Notebooks/05-Unit-Commitment.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Unit Commitment\n",
    "\n",
    "_**[Power Systems Optimization](https://github.com/east-winds/power-systems-optimization)**_\n",
    "\n",
    "_by Michael R. Davidson and Jesse D. Jenkins (last updated: October 11, 2022)_\n",
    "\n",
    "This notebook will build on the economic dispatch (ED) model by introducing binary startup (called \"commitment\") decisions, constraints, and costs of thermal generators. Similar to ED, it minimizes the short-run production costs of meeting electricity demand, but these additions are necessary for operating systems with large amounts of (inflexible) thermal generation. They also entail significant computational trade-offs.\n",
    "\n",
    "****\n",
    "\n",
    "We build up the model in several stages. We first start with the simplest model that incorporates unit commitment decisions in order to understand the logic of three-variable commitment formulations.\n",
    "\n",
    "Next, we introduce moderate complexity through the addition of ramp constraints&mdash;which we need to be modified from the ED to account for startups and shutdowns.\n",
    "\n",
    "Finally, we model a more realistic unit commitment that includes reserves&mdash;an important feature of day-ahead scheduling in power systems."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction to unit commitment\n",
    "\n",
    "Engineering considerations severely limit the possible output ranges of power plants. System operators need to be aware of these limitations when scheduling generation to meet demand. Thermal power plants, in particular, due to their complex designs, thermodynamic cycles, and material properties, can be particularly challenging. In practice, due to the times involved in bringing these power plants online, much of this scheduling is done day-ahead, which gives rise to the need for a day-ahead market.\n",
    "\n",
    "**Unit commitment** (UC) is the problem of minimizing short-run costs of production inclusive of production and startup costs, in order to meet a given demand and considering relevant engineering constraints of the generators. It is built on the ED model in that it typically considers all of the same variables in addition to the new startup-related variables and constraints&mdash;hence, it is also sometimes called unit commitment and economic dispatch (UCED). This notebook, for simplicity, only considers a single-bus case, while typical formulations usually include a simplified network representation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple unit commitment\n",
    "\n",
    "We start with the simplest case that incorporates unit commitment, building on the `economic_dispatch_multi` problem of the [Economic Dispatch notebook](04-Economic-Dispatch.ipynb).\n",
    "\n",
    "\n",
    "$$\n",
    "\\begin{align}\n",
    "\\min \\ & \\sum_{g \\in G, t \\in T} VarCost_g \\times GEN_{g,t} + \\sum_{g \\in G_{thermal}, t \\in T} StartUpCost_g \\times START_{g,t} \\\\\n",
    "\\end{align}\n",
    "$$\n",
    "$$\n",
    "\\begin{align}\n",
    "\\text{s.t.} & \\\\\n",
    " & \\sum_{g} GEN_{g,t} = Demand_t & \\forall \\quad t \\in T \\\\\n",
    " & GEN_{g,t} \\leq Pmax_{g,t} & \\forall \\quad g \\notin G_{thermal} , t \\in T \\\\\n",
    " & GEN_{g,t} \\geq Pmin_{g,t} & \\forall \\quad g \\notin G_{thermal} , t \\in T \\\\\n",
    " & GEN_{g,t} \\leq Pmax_{g,t} \\times COMMIT_{g,t} & \\forall \\quad g \\in G_{thermal} , t \\in T \\\\\n",
    " & GEN_{g,t} \\geq Pmin_{g,t} \\times COMMIT_{g,t} & \\forall \\quad g \\in G_{thermal} , t \\in T \\\\\n",
    " & COMMIT_{g,t} \\geq \\sum_{t'≥t-MinUp_g}^{t} START_{g,t} & \\forall \\quad g \\in G_{thermal} , t \\in T \\\\\n",
    " & 1-COMMIT_{g,t} \\geq \\sum_{t'≥t-MinDown_g}^{t} SHUT_{g,t} &\\forall \\quad g \\in G_{thermal} , t \\in T \\\\\n",
    "  & COMMIT_{g,t+1} - COMMIT_{g,t} =&\\\\\n",
    " & \\quad START_{g,t+1} - SHUT_{g,t+1} &\\forall \\quad G_{thermal} \\in G , t = 1..T-1 \n",
    "\\end{align}\n",
    "$$\n",
    "\n",
    "\n",
    "The **decision variables** in the above problem:\n",
    "\n",
    "- $GEN_{g}$, generation (in MW) produced by each generator, $g$\n",
    "- $START_{g,t}$, startup decision (binary) of thermal generator $g$ at time $t$\n",
    "- $SHUT_{g,t}$, shutdown decision (binary) of thermal generator $g$ at time $t$\n",
    "- $COMMIT_{g,t}$, commitment status (binary) of generator $g$ at time $t$\n",
    "\n",
    "The **parameters** are:\n",
    "\n",
    "- $Pmin_g$, the minimum operating bounds for generator $g$ (based on engineering or natural resource constraints)\n",
    "- $Pmax_g$, the maximum operating bounds for generator $g$ (based on engineering or natural resource constraints)\n",
    "- $Demand$, the demand (in MW)\n",
    "- $VarCost_g = VarOM_g + HeatRate_g \\times FuelCost_g$, the variable cost of generator $g$ \n",
    "- $StartUpCost_g$, the startup cost of generator $g$\n",
    "- $MinUp_g$, the minimum up time of generator $g$, or the minimum time after start-up before a unit can shut down\n",
    "- $MinDown_g$, the minimum down time of generator $g$, or the minimum time after shut-down before a unit can start again\n",
    "\n",
    "In addition, we introduce a few different sets:\n",
    "\n",
    "- $G$, the set of all generators\n",
    "- $G_{thermal} \\subset G$, the subset of thermal generators for which commitment is necessary\n",
    "- $T$, the set of all time periods over which we are optimizing commitment and dispatch decisions\n",
    "\n",
    "Finally, the **three-variable commitment equations** capture the basic logic of commitment:\n",
    "\n",
    "- Units incur costs when they startup (not when they shutdown)\n",
    "- Units must stay on (and off) for a minimum period of time&mdash;in lieu of explicitly enforcing a startup trajectory\n",
    "- Some summations (simplified here) will need to be modified near the beginning of the time period\n",
    "\n",
    "There are some further resources at the bottom for alternative and/or more complex formulations of the UC.\n",
    "\n",
    "Now, let's implement UC."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Load packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "using JuMP, HiGHS\n",
    "using Plots;\n",
    "using VegaLite  # to make some nice plots\n",
    "using DataFrames, CSV, PrettyTables\n",
    "ENV[\"COLUMNS\"]=120; # Set so all columns of DataFrames and Matrices are displayed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Load and format data\n",
    "\n",
    "We will use data loosely based on San Diego Gas and Electric (SDG&E, via the [PowerGenome](https://github.com/gschivley/PowerGenome) data platform) including a few neighboring generators and adjustments to make the problem easy to solve, consisting of:\n",
    "\n",
    "- 33 generators (we added a few more to ensure we can provide enough reserves)\n",
    "- estimated hourly demand for 2020 (net load at the transmission substation level after subtracting 600MW of behind-the-meter solar from original demand)\n",
    "- variable generation capacity factors\n",
    "- estimated natural gas fuel costs\n",
    "\n",
    "In order to demonstrate the impacts of unit commitment, we will keep our high solar sensitivity case from the [Economic Dispatch notebook](04-Economic-Dispatch.ipynb) (with 3,500 MW of solar PV) to produce large variations in net load (demand less available renewable supply) required to meet demand (similar to [California's infamous \"Duck Curve\"](https://www.caiso.com/Documents/FlexibleResourcesHelpRenewables_FastFacts.pdf)). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "datadir = joinpath(\"uc_data\") \n",
    "gen_info = CSV.read(joinpath(datadir,\"Generators_data.csv\"), DataFrame);\n",
    "fuels = CSV.read(joinpath(datadir,\"Fuels_data.csv\"), DataFrame);\n",
    "loads = CSV.read(joinpath(datadir,\"Demand.csv\"), DataFrame);\n",
    "gen_variable = CSV.read(joinpath(datadir,\"Generators_variability.csv\"), DataFrame);\n",
    "\n",
    "# Rename all columns to lowercase (by convention)\n",
    "for f in [gen_info, fuels, loads, gen_variable]\n",
    "    rename!(f,lowercase.(names(f)))\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Construct generator dataframe**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Keep columns relevant to our UC model \n",
    "select!(gen_info, 1:26) # columns 1:26\n",
    "gen_df = outerjoin(gen_info,  fuels, on = :fuel) # load in fuel costs and add to data frame\n",
    "rename!(gen_df, :cost_per_mmbtu => :fuel_cost)   # rename column for fuel cost\n",
    "gen_df.fuel_cost[ismissing.(gen_df[:,:fuel_cost])] .= 0\n",
    "\n",
    "# create \"is_variable\" column to indicate if this is a variable generation source (e.g. wind, solar):\n",
    "gen_df[!, :is_variable] .= false\n",
    "gen_df[in([\"onshore_wind_turbine\",\"small_hydroelectric\",\"solar_photovoltaic\"]).(gen_df.resource),\n",
    "    :is_variable] .= true;\n",
    "\n",
    "# create full name of generator (including geographic location and cluster number)\n",
    "#  for use with variable generation dataframe\n",
    "gen_df.gen_full = lowercase.(gen_df.region .* \"_\" .* gen_df.resource .* \"_\" .* string.(gen_df.cluster) .* \".0\");\n",
    "\n",
    "# remove generators with no capacity (e.g. new build options that we'd use if this was capacity expansion problem)\n",
    "gen_df = gen_df[gen_df.existing_cap_mw .> 0,:];"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Modify load and variable generation dataframes**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1. Convert from GMT to GMT-8\n",
    "gen_variable.hour = mod.(gen_variable.hour .- 9, 8760) .+ 1 \n",
    "sort!(gen_variable, :hour)\n",
    "loads.hour = mod.(loads.hour .- 9, 8760) .+ 1\n",
    "sort!(loads, :hour);\n",
    "\n",
    "# 2. Convert from \"wide\" to \"long\" format\n",
    "gen_variable_long = stack(gen_variable, \n",
    "                        Not(:hour), \n",
    "                        variable_name=:gen_full,\n",
    "                        value_name=:cf);\n",
    "# Now we have a \"long\" dataframe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Create solver function"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a utility function, since we do this alot, we'll create a function to convert JuMP AxisArray outputs with two indexes to DataFrames."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "value_to_df_2dim (generic function with 1 method)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#=\n",
    "Function to convert JuMP outputs (technically, AxisArrays) with two-indexes to a dataframe\n",
    "Inputs:\n",
    "    var -- JuMP AxisArray (e.g., value.(GEN))\n",
    "Reference: https://jump.dev/JuMP.jl/v0.19/containers/\n",
    "=#\n",
    "function value_to_df_2dim(var)\n",
    "    solution = DataFrame(var.data, :auto)\n",
    "    ax1 = var.axes[1]\n",
    "    ax2 = var.axes[2]\n",
    "    cols = names(solution)\n",
    "    insertcols!(solution, 1, :r_id => ax1)\n",
    "    solution = stack(solution, Not(:r_id), variable_name=:hour)\n",
    "    solution.hour = foldl(replace, [cols[i] => ax2[i] for i in 1:length(ax2)], init=solution.hour)\n",
    "    rename!(solution, :value => :gen)\n",
    "    solution.hour = convert.(Int64,solution.hour)\n",
    "    return solution\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we'll create a function to create and solve a simple unit commitment problem with specified input data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "unit_commitment_simple (generic function with 1 method)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#=\n",
    "Function to solve simple unit commitment problem (commitment equations)\n",
    "Inputs:\n",
    "    gen_df -- dataframe with generator info\n",
    "    loads  -- load by time\n",
    "    gen_variable -- capacity factors of variable generators (in \"long\" format)\n",
    "    mip_gap -- desired relative MIP gap to pass to solver\n",
    "=#\n",
    "function unit_commitment_simple(gen_df, loads, gen_variable, mip_gap)\n",
    "    UC = Model(HiGHS.Optimizer)\n",
    "    set_optimizer_attribute(UC, \"mip_rel_gap\", mip_gap)\n",
    "\n",
    "    # Define sets based on data\n",
    "    # Note the creation of several different sets of generators for use in\n",
    "    # different equations.\n",
    "        # Thermal resources for which unit commitment constraints apply\n",
    "    G_thermal = gen_df[gen_df[!,:up_time] .> 0,:r_id] \n",
    "        # Non-thermal resources for which unit commitment constraints do NOT apply \n",
    "    G_nonthermal = gen_df[gen_df[!,:up_time] .== 0,:r_id]\n",
    "        # Variable renewable resources\n",
    "    G_var = gen_df[gen_df[!,:is_variable] .== 1,:r_id]\n",
    "        # Non-variable (dispatchable) resources\n",
    "    G_nonvar = gen_df[gen_df[!,:is_variable] .== 0,:r_id]\n",
    "        # Non-variable and non-thermal resources\n",
    "    G_nt_nonvar = intersect(G_nonvar, G_nonthermal)\n",
    "        # Set of all generators (above are all subsets of this)\n",
    "    G = gen_df.r_id\n",
    "        # All time periods (hours) over which we are optimizing\n",
    "    T = loads.hour\n",
    "        # A subset of time periods that excludes the last time period\n",
    "    T_red = loads.hour[1:end-1]  # reduced time periods without last one\n",
    "\n",
    "    # Generator capacity factor time series for variable generators\n",
    "    gen_var_cf = innerjoin(gen_variable, \n",
    "                    gen_df[gen_df.is_variable .== 1 , \n",
    "                        [:r_id, :gen_full, :existing_cap_mw]], \n",
    "                    on = :gen_full)\n",
    "        \n",
    "    # Decision variables   \n",
    "    @variables(UC, begin\n",
    "            # Continuous decision variables\n",
    "        GEN[G, T]  >= 0     # generation\n",
    "            # Bin = binary variables; \n",
    "            # the following are all binary decisions that \n",
    "            # can ONLY take the values 0 or 1\n",
    "            # The presence of these discrete decisions makes this an MILP\n",
    "        COMMIT[G_thermal, T], Bin # commitment status (Bin=binary)\n",
    "        START[G_thermal, T], Bin  # startup decision\n",
    "        SHUT[G_thermal, T], Bin   # shutdown decision\n",
    "    end)\n",
    "                \n",
    "    # Objective function\n",
    "        # Sum of variable costs + start-up costs for all generators and time periods\n",
    "    @objective(UC, Min, \n",
    "        sum( (gen_df[gen_df.r_id .== i,:heat_rate_mmbtu_per_mwh][1] * gen_df[gen_df.r_id .== i,:fuel_cost][1] +\n",
    "            gen_df[gen_df.r_id .== i,:var_om_cost_per_mwh][1]) * GEN[i,t] \n",
    "                        for i in G_nonvar for t in T) + \n",
    "        sum(gen_df[gen_df.r_id .== i,:var_om_cost_per_mwh][1] * GEN[i,t] \n",
    "                        for i in G_var for t in T)  + \n",
    "        sum(gen_df[gen_df.r_id .== i,:start_cost_per_mw][1] * \n",
    "            gen_df[gen_df.r_id .== i,:existing_cap_mw][1] *\n",
    "            START[i,t] \n",
    "                        for i in G_thermal for t in T)\n",
    "    )\n",
    "    \n",
    "    # Demand balance constraint (supply must = demand in all time periods)\n",
    "    @constraint(UC, cDemand[t in T], \n",
    "        sum(GEN[i,t] for i in G) == loads[loads.hour .== t,:demand][1])\n",
    "\n",
    "    # Capacity constraints \n",
    "      # 1. thermal generators requiring commitment\n",
    "    @constraint(UC, Cap_thermal_min[i in G_thermal, t in T], \n",
    "        GEN[i,t] >= COMMIT[i, t] * gen_df[gen_df.r_id .== i,:existing_cap_mw][1] *\n",
    "                        gen_df[gen_df.r_id .== i,:min_power][1])\n",
    "    @constraint(UC, Cap_thermal_max[i in G_thermal, t in T], \n",
    "        GEN[i,t] <= COMMIT[i, t] * gen_df[gen_df.r_id .== i,:existing_cap_mw][1])\n",
    "\n",
    "      # 2. non-variable generation not requiring commitment\n",
    "    @constraint(UC, Cap_nt_nonvar[i in G_nt_nonvar, t in T], \n",
    "        GEN[i,t] <= gen_df[gen_df.r_id .== i,:existing_cap_mw][1])\n",
    "    \n",
    "      # 3. variable generation, accounting for hourly capacity factor\n",
    "    @constraint(UC, Cap_var[i in 1:nrow(gen_var_cf)], \n",
    "            GEN[gen_var_cf[i,:r_id], gen_var_cf[i,:hour] ] <= \n",
    "                        gen_var_cf[i,:cf] *\n",
    "                        gen_var_cf[i,:existing_cap_mw])\n",
    "    \n",
    "    # Unit commitment constraints\n",
    "      # 1. Minimum up time\n",
    "    @constraint(UC, Startup[i in G_thermal, t in T],\n",
    "        COMMIT[i, t] >= sum(START[i, tt] \n",
    "                        for tt in intersect(T,\n",
    "                            (t-gen_df[gen_df.r_id .== i,:up_time][1]):t)))\n",
    "\n",
    "      # 2. Minimum down time\n",
    "    @constraint(UC, Shutdown[i in G_thermal, t in T],\n",
    "        1-COMMIT[i, t] >= sum(SHUT[i, tt] \n",
    "                        for tt in intersect(T,\n",
    "                            (t-gen_df[gen_df.r_id .== i,:down_time][1]):t)))\n",
    " \n",
    "      # 3. Commitment state\n",
    "    @constraint(UC, CommitmentStatus[i in G_thermal, t in T_red],\n",
    "        COMMIT[i,t+1] - COMMIT[i,t] == START[i,t+1] - SHUT[i,t+1])\n",
    "    \n",
    "    # Solve statement (! indicates runs in place)\n",
    "    optimize!(UC)\n",
    "\n",
    "    # Generation solution and convert to data frame \n",
    "    # with our helper function defined above\n",
    "    gen = value_to_df_2dim(value.(GEN))\n",
    "\n",
    "    # Commitment status solution and convert to data frame\n",
    "    commit = value_to_df_2dim(value.(COMMIT))\n",
    "\n",
    "    # Calculate curtailment = available wind and/or solar output that \n",
    "    # had to be wasted due to operating constraints\n",
    "    curtail = innerjoin(gen_var_cf, gen, on = [:r_id, :hour])\n",
    "    curtail.curt = curtail.cf .* curtail.existing_cap_mw - curtail.gen\n",
    "    \n",
    "    # Return the solution parameters and objective\n",
    "    return (\n",
    "        gen,\n",
    "        commit,\n",
    "        curtail,\n",
    "        cost = objective_value(UC),\n",
    "        status = termination_status(UC)\n",
    "    )\n",
    "\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. Solve a day's unit commitment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running HiGHS 1.5.3 [date: 1970-01-01, git hash: 45a127b78]\n",
      "Copyright (c) 2023 HiGHS under MIT licence terms\n",
      "Presolving model\n",
      "2598 rows, 2177 cols, 8905 nonzeros\n",
      "2309 rows, 1827 cols, 10164 nonzeros\n",
      "\n",
      "Solving MIP model with:\n",
      "   2309 rows\n",
      "   1827 cols (1251 binary, 0 integer, 0 implied int., 576 continuous)\n",
      "   10164 nonzeros\n",
      "\n",
      "        Nodes      |    B&B Tree     |            Objective Bounds              |  Dynamic Constraints |       Work      \n",
      "     Proc. InQueue |  Leaves   Expl. | BestBound       BestSol              Gap |   Cuts   InLp Confl. | LpIters     Time\n",
      "\n",
      "         0       0         0   0.00%   0               inf                  inf        0      0      0         0     0.0s\n",
      "         0       0         0   0.00%   853832.31776    inf                  inf        0      0      6       644     0.0s\n",
      " R       0       0         0   0.00%   853908.886691   862256.418938      0.97%      188     15     21       691     0.0s\n",
      "\n",
      "Solving report\n",
      "  Status            Optimal\n",
      "  Primal bound      862256.418938\n",
      "  Dual bound        853908.886691\n",
      "  Gap               0.968% (tolerance: 1%)\n",
      "  Solution status   feasible\n",
      "                    862256.418938 (objective)\n",
      "                    0 (bound viol.)\n",
      "                    0 (int. viol.)\n",
      "                    0 (row viol.)\n",
      "  Timing            0.04 (total)\n",
      "                    0.01 (presolve)\n",
      "                    0.00 (postsolve)\n",
      "  Nodes             1\n",
      "  LP iterations     691 (total)\n",
      "                    0 (strong br.)\n",
      "                    47 (separation)\n",
      "                    0 (heuristics)\n"
     ]
    }
   ],
   "source": [
    "# A spring day\n",
    "n=100\n",
    "T_period = (n*24+1):((n+1)*24)\n",
    "\n",
    "# High solar case: 3,500 MW\n",
    "gen_df_sens = copy(gen_df)\n",
    "gen_df_sens[gen_df_sens.resource .== \"solar_photovoltaic\",\n",
    "    :existing_cap_mw] .= 3500\n",
    "\n",
    "loads_multi = loads[in.(loads.hour,Ref(T_period)),:]\n",
    "gen_variable_multi = gen_variable_long[in.(gen_variable_long.hour,Ref(T_period)),:]\n",
    "\n",
    "# Note we reduce the MIP gap tolerance threshold here to increase tractability\n",
    "# Here we set it to a 1% gap (mip_gap=0.01), meaning that we will terminate once we have \n",
    "# a feasible integer solution guaranteed to be within 1% of the objective\n",
    "# function value of the optimal solution (e.g. the upper and lower bound are within 1% of\n",
    "# each other as HiGHS traverses the branch and bound tree).\n",
    "# HiGHS's default MIP gap is 0.0001 (0.01%), which can take a longer time for \n",
    "# any complex problem. So it is important to set this to a realistic value.\n",
    "# For a list of all solver options implemented via HiGHS.jl see \n",
    "# https://github.com/jump-dev/HiGHS.jl\n",
    "solution = unit_commitment_simple(\n",
    "    gen_df_sens, loads_multi, gen_variable_multi, 0.01); #1% MIP Gap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
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Pi6hVMxQhD1F8H0La6TYMD73LL5Y7ed/hEWaG5U/P+j/KYvzX19l1M6rceiJ1i0ObitfCulaiTjFt27YlKyuL/Px8ABYsWEBAQABmZmaaKUcfH59y2zh//jxt27bl3LlzrFq1StNWaUjKCWk1MzOjdevWbNu2DQ8PD5YsWaIZ7ZV2XnltidRvxBFhYyXAQ2vzvEzXiIIbdacFqkxMQumljlwd2zkT12cdONRxBIfjzcpUoimUK/n0ZAhB8dlsmd6n3oThizxm9nO23I8rX5/2pYG2lW5PX1+fzz77DBcXFzp06ICJiQm9evVi1qxZTJ06FRsbmzJHX7169WLJkiX8+uuvrFq1irlz5yKXy+nRowf79++v0nUVs3XrVtzc3HB0dCQ4OBgvLy+io6PL7P/9999n+PDhYraLBkaN5CP08vJiw4YNyGQynJ2d+eqrr7SmJ4qKinjllVfw8fHB1taW3bt307p1a27dusVbb71FYWEhixcv5s0330QQBD744APOnDmDlZUVP/30Ew4ODuX2L+YjBH4YDCkhmreP9CaQ+8v9munr36KjQ26/AezuM52zpSe80LBuSi/mDupY5vH6kOevMtQHO6vTBpUg8K6HP55+8aUef7FvO/433QmdUp5iSttqYGtrS9euXcnPzycvL08rP2F2djY6OjrlpmbKycmhWbNmFBQUkJmZSbt27ZBKpSgUiiqldHqSvLw84uPjsbe3rzCpb25urmavokjDodqnRpVKJa+99hpHjx7F29ubBw8elPjA//DDDxgZGREYGMjkyZP56KOPUKlULFiwgN27d+Pj48OePXsICgrC09OTkJAQAgICWLlyJa+99lp1m9z4SPTXcoJFemZIr9TDvXoqFebef/LGT++xTuaPpYl+mVXXnw4lIrXyQRcitYOORMLWGX3YOqMPAzpZYmKgi4mBLgM6WbJ1Rh+2TO9TqhOsCFNT0xJJei0sLCp0ZsWZ7E1MTDTTmMbGxv/aCYJ6irRbt26Vymxvbm4uOsEGSLVPjSoUCrZu3Uq7du2QyWRIpVLNh7OYM2fO8Nln6lRA06dPZ+PGjYSGhtKyZUscHR0BmDx5MhcuXCAoKIh58+aho6ODm5sbc+bMQalUVupD2WS5f1DrbbLSFcUj3zoypnL0O7OfH62v8sPzb3MltWTCYKlcyZuH7+O5bAj6uuLSdn1CIlGP/F7sW7VoydGjR9eQRSIiVaPaf1EMDQ1xd3fn3LlzdO/enYyMjBLz5UlJSZqnPUtLSzIzM0lKSqJt27aaOlZWVqSlpWnVlUgkWFhYkJVV/ppEk0algOBjmrcFRi0puly1fVx1hXliLB/89DZrhDBMDUo+owXFZ/P1xYd1YJmIiEhjpkZGhEVFRbi5uREZGcnKlSv54osv2LBhg6aOubk56enpdO7cmYKCAszNzTEzM9PaL5SXl6eZCklPT9eU5+fna01z3Lhxg5s3b5awI7KBZEyvbjtN4q7QNu/xNOij1L4ok4KrtY+aZsiJn7Hr2I0tw18m8B/xPT9cjsDORIaTTcltFU31fy4iIvJ0VLsj/Ouvv5g3bx737t0D1Pt04uO1F9L79euHj48P/fv3586dOwwaNIiePXsSExNDfn4+pqam3L59mxUrViCRSPDx8WHatGmEh4dja2uLgYGBpi1nZ2ecnZ212t+8eXOdByRUhhoJnPD5WPNnnnFbOF+2/FV9pk3MX2w8uJKzs95lh7QNcqU6slQlCGy9lcbZN3toybHVhyCUylAf7Kx2RywI4H8QfHZD8t/SfW16Qf//A6fZ1Ha4b2RkJG3atMHUtO72oAYFBeHo6Fip9cLIyEisra0xNjZ+6n7T09ORyWRYW1trlT98+JAOHTpgZGT01H00Rqp9atTR0RE7OzsmTJjA0qVL2bFjB8uWLePRo0e0aNECgDfffJOtW7eyePFili9fzkcffYS5uTkvv/wyI0eOZPr06ejo6ODs7Mz//d//4eXlxcKFC5kyZQrr1q2rbpMbD9JMeHBO8zYj6zmUGZl1aNDToatQ8Pwvm/ku9iStTR8H0sRlFPCJV8Ma5TZaBBUcWwLHl8Ejb5BL1a9H3uqyY0vUdWqRDz74gJCQkIor1iAffvghCoWiUnU/+OADIiLK3t/74YcfkplZue/xmTNn+Pnnn0uUf/nllyQmJlaqjaZIjewj9PDwIDQ0FKlUytdff42RkREqlYo333wTAHt7e3x8fAgMDOSLL77A0tISgP/+97/MnDmT/Px8nn32WSQSCS1btsTX15d79+6xadMmrXVEkX8QdBQURQDkmNgiPRNWxwZVD7bel/lekctH/RbwV5r6+o74PmJEt9Y8/4x1BWeL1Ch++yHwSNnHA49AZxfou6BKzfr4+BAdHa2RLSsWupbJZISHhzN06FCaNWuGIAhcvnyZgoICXFxcNIF5hYWFnDx5EhsbG/r16weot21dvHgRgDFjxqCvr098fDwmJibcvXuXMWPGoFAouH79OqampgwcOLBMVZqYmBjMzc2xtLQkIiKCFi1aYGlpSUxMDJaWlmzYsAE9PT2ioqJo2bIlPj4+mJmZMXDgQI19d+7cqTAVVGJiIl5eXowcOZLBgweTlJSEnZ2d+tYGBtK7d29iYmKwsLDg7t27mvNu3LhBQUEBI0eORE9Pj7fffhtra2sSEhIwNjYmNDQUmUyGi4uL5hrv3btHeno6Q4cO1QiONxVqJPxOIpHQs2dP+vXrpxmK5+fnM3bsWE2dZs2aMXToUI0TLKZbt2707dtXa0rByMiIIUOGiE6wIvwPaf7MSH4WVU7FOpANBTM/H7b472GgzeOR4WrPQBKzpXVolQj39lVPnSfYuHEj69evJyYmhrFjxxIYGIi/vz+jRo1i06ZNGqFrgDfeeAMPDw+CgoIYOXIkMplaQnDVqlX4+/uzdOlSvLy8UCgUjBkzhps3b3Lt2jVcXV2Ry+X88MMPjB07ll9++QWZTMa4ceP4448/2LVrF7Nnzy7TRk9PT77//nsAJk2axNdffw3AnDlzKCgoYPLkycjlclavXs2kSZO4fv06r776Kr/99htKpZKxY8dy9OhRPvvsM27cuFFmP5GRkeTk5HD79m1CQkJ49913NccmTZqEIAisX7+eCRMmcPz4cUAtSu7l5cXhw4eZOnUqAMuWLSMqKooff/yRMWPGcPLkSdavX8/mzZsB9ajziy++4MaNG7i4uGjFZTQFak1ZxtzcnCFDhtRWd02P9HD4e4tEhlk3io5XT9Ld+oSuty8b9AW+HjCLkzE6ZEvlvH8kgH2Lnqtr05ouKZWYgkypvMh7sU5oeHg4enp6tG3blu+++4758+djbW2tEbq2tbVFqVTi5+fHggULmD17NmPHjkX1d47Nt99+m2nTptG5c2euXr0KQNeuXVm/fj0A7u7umv3NU6ZMYfXq1Rw+fJhevXqxadMmQB1/EB4ejr29fQk7x48fz2uvvUZSUhIdOnTg+vXr5ObmolKpSux/XLZsGTNnzsTR0ZFr165hYmJCx44d+fbbbwEYMGBAmfdj6NChWFtbs3jx4hKxFk+ycOFC/vOf/7B//37Gjx/P559/DkDfvn2JitKWKZw6dSqrV6/m/v37fPjhhyxatIhTp07h7++PRCJBIpHw22+/8corr5TZX2ND3JDVWLh/EFCLBGVHd0X1hDBxY0J+6x7vhv7Gmw7qyNjrD9PYfUvUI607KiO6XflgmeTkZKytrdHTUz+jd+rUidRUtexQaULX+/btIygoiIEDB7Jp0yaN/FpxXVNTU6RSKdHR0XTt2lVz/pNZLYozTURFRXH16lVmzJjBjBkzypVz69atGykpKVy8eJGpU6cil8s5d+6c1qxXMe3btwfUG/OlUimRkZFazrU04fDK8KT4ePE1PNkfqB8YitNXFVN8b4rtiY2NJTU1lZkzZzJjxgxCQkJKzNQ1dkRH2BgQVBDwKwAZZk4UXfGvY4NqFul5b6b+dYU19pHoSCRsPhtGaIo4RVontO5RcZ1WlajzN23btiUhIYGCggIAvL29cXJyAkoXtd6yZQtfffUVwcHB6OnpcefOnVLr2tvbc//+Y4nBu3fv8swzz2jVcXBwoF+/fnh4eODh4UG7du3KTak0fPhwtm7diqurK87OzmzYsIEJEyaUqPdPWxwcHPDz8wPUSlxP2lUeTwqPx8bGkpycXGo9b29vAORyOQ8ePKhQkrJTp06Ym5tz6NAhPDw8GDduXJNLJSU6wsZA1HXIfgRA1oN2CJWMVmvISL3uMiral22dryGRSFh1Nk6UYKsL+i2sRJ3KB8ro6+uzZs0ahg8fzvz58zly5AjLly8vs76FhQVubm4sWrSI2NhYTZqkfzJu3DgKCwuZMmUKbm5u9OnTR+Ngi5k6dSoZGRlMmzaNUaNGYWhoWEIV60nGjx9PUlIS3bp1Y/To0cTHx9O/f/8Kr9HNzQ0dHR0mTpzICy+8QPPmzcut37t3b5YsWULXrl3Jy8tj4sSJ/Oc//8HWtnQx88TERMaPH8/QoUNZvnx5udcA0KpVK5YuXcrw4cOZNWsWBw4coG/fvhVeR2OiRkS365omJ7p9/FW4f5Ak80Fk7nwEqtoNV68zJBL0Zvcjy1KPJSkzMDcx5NiyobQ2N6xry8qkvuwjrDYbBBV4vqKZkSiB0yyYsg0kJZ+5yxPdzs7OJiMjg06dOlW4Fy8xMZHs7GwcHBwqlF6MjY3F1NSUli1bllknJiYGY2NjWrduTVpaWqkjtr59+z719GF0dDRt27bFyMiIvLw8zWj2SXr06IGNjQ15eXkaIZHExERat25d7rWmpaVhYGBQoRN8kszMTNLT00tdE23siCPCho6sAEJOICChwL9Z03GCAIKA4rAfVjlyPE02YKKjZN7Pf5ItFZOk1hoSHZi6Xf2yHQwGJuqX7WB12ZQfS3WCFWFhYUHnzp0rtSHd2tqa7t27V0p/2NbWtlwnCOqM861bt660rf+WTp06VWqDu0Qi0VLTsra2rvBaraysquQEAVq0aNEknSCI+QgbPqEnQJZPkulwiu4G1bU1tY9SSdHBABQzuuCp+ypvmX3Lf/b7sm/RQAz1xOe8WkEiUY/8nGZV6bSGILptZWVVK3aamZk1iPvRWBF/KRo69w+i0tEj36fpZuMQ5HJ0j0STYtyXH1Pm0VcSzuuH/FCqGt2sv4iISA0gOsKGTE4CxNwk0dAVuX/jUJH51xQVITsQSZyFMx/EL2ei9BTrTzW+vZQiIiLVj+gIGzL+h1Cgh/SmuHUAQJWXT9HBeOLNnXkhYSsT47bgcVPUJK1pBAROhJ9gzpk59P+lP/1/6c+cM3M4EX4CgbodlQcGqh+GoqKiyM/Pr7BeVQkOfrrPV3Z2NrGx1ZMmLSUlhaSkpGppq6khOsKGTOBvJOuOQv5ATOtTjConj/yjmTxqPoh+qcdxub2YkACfujar0aISVKy8tpKPbn5EQGoARcoiipRFBKQG8NHNj1h5bSWqWhbdfpJJkyYBagmxgICACutVFXd39391XjHXr1/XqMBUlmvXrnHw4MES5ZcuXeLcuXOlnCFSEaIjbKgkB1OUGUvBtaalCVgZlBmZ5HtKSbR4lrZ5odiddkfxl/gDURN4hntyJupMmcfPRJ3BM9yzSm3K5XLOnj3L77//TlGRWmQ9LCyMzMxMjh8/TkxMDFlZWZw5c0ZrNBUTE8PRo0e1xKerQkpKCp6enpo0VSEhIRr1FplMRlCQOhgtPT2dixcvauVPffDgAVlZWRo5t4SEBI4cOaJJR1dMUFAQv//+Ozk5/0i0CQiCwI0bN7h27ZpGMxXU211+/fVXwsLCUCgUXL16lT/++IOMjAwePHhAdnY2V65cYeTIkbi5uQGQm5vL8ePHuXTpEo1wh1y1IzrChkrQEVIVI1HExNW1JfUSVXIqead1SWnWA8OiTPR+nQ3+h+varEbHsQfHqqXOk0ybNo3r169z69YtJk6cCMD8+fNZtGgRfn5+uLi4sHDhQm7durM6SOEAACAASURBVIWrqys5OTncv3+fF198kfj4eNauXcuWLVuq1KdSqWTZsmWEhoYyZswYYmJi2LJlC0ePHgXU6Y02b95MdHQ0Li4uXLt2jcWLF5Obqxa2X7p0KTNmzODatWv4+/vz/PPPExsby5o1azTC1l988QUfffQR3t7ejBgxgrg47e/uzJkzOXz4MF5eXri5uaFQKLh48SLu7u7ExsYyY8YMrl69SnBwMNHR0SQmJrJs2TLc3d25evUqhw8fZu/eveTl5eHs7Mz9+/fZsWMH7733XpXuRVNE3D7RQBFCTlD4Z6u6NqNeo3iUQPYFWySju9Iq54F643d+Cgx5o65NazQ8zHpYYZ3wrPAqtRkYGMiSJUtwc3PD19dXU/7RRx/Rr18/rl69yjvvvIOLiwshISGEhoZibm7Onj176NChAwYGBpqRWWVRqVR888032NjYkJCQgI+PD3PmzOHbb79lzpw5HDlyhLlz5/LDDz/w9ttvs2TJErKysujR47F83KpVq3B1dWXu3Lls3LgRNzc3li1bRvv27Xn99dfZvn07YWFh6OnpYWFhwf79+zUyb7dv36aoqIjvvvsOUGexuHr1Khs3buSrr77CxcWFESNGkJmZycSJEwkNDcXR0RFQ5zMcPXo033zzDQC//PILLi4ufPLJJ0ilUrZt21ale9EUEUeEDZFHPmRLTZFHVs8ie2NGERlL1mUrMkw7AgKcXwOXPqtrsxoNkkqIbldmU/yTnDhxAi8vL5ycnNizZ48mwW2xmLShoaFmU7yuri5FRUWkp6ezePFili5dWmntzifR09PDxsYGUAt1FxQUMGLECIKDg0lLS8Pb25vRo0drCWY3b95ck2wcHgtfx8TEaAS+jYyMMDMzIzIykszMTGbPns2MGTO4ceOGVlq5qKgoQkJCNILfcrkcAwMDYmJiNM52wIABpYp6Pym4Xdx/z549ATA2Nuadd96p8v1oaoiOsCESdJSCzI51bUWDQfEwmow7nck1Uf/Qce1/6uzpqsavyVrT2DevWInErrldpduTSqXs3buXn3/+WTPaK87eXp5D/fbbb/nss8/49ddfGTx4cKX7K6a0tnV0dJg6dSpvvPEGEydORE9PT0swOzY2VmudsBg7OzuNM46Pj8fU1BQ7OzvMzMzYt28fHh4euLu7awlbOzg4YGtrqxH87tOnDzY2Njg4OBAWpt4atW3bNnbs2AFQ7rpf165dCQ1Vp76KiorixRdfrPL9aGqIU6MNDUEFIceRBtetXmVDQx78gGTDnug4FWIqzYD7B6AwG9x3gl7FMlcipePe1Z2AtLKjMQHcHSofWWlsbExycjIvvvgipqammJmZVUr2a8KECaxYsYK9e/fSvHlzvL29CQ+v2pRsacyZM4c+ffpoIk7ffvttxo4di4+PD1KplFatSi5PrF69munTp+Pl5YW/vz9btmzB2NiYNWvWMGLECOzt7YmKiuLMmTNcv34dUI/2unfvzrhx49DX18fCwoIuXbqwYcMGFixYgKOjIxEREZw6dYrY2Fg+/PDDUjNdAMyePZuDBw/i7u5OTEwMH3/88VPfh8aOKLpdh/wr8eOo62Qd+YDEXVnQ+P51NY7BECfa29/AUKYOcqDzMJh1GAzNaqX/xia6rRJUrL6xmlORp0o9PsluEuuGrkOniqLbMTExKBQKunTpUump1eTkZIyNjWnWrBkZGRlYWFhoaXIWFRVpHM+TODg40LFj6TMs8fHxLFq0SGtbgkKhIC4ujo4dO6KjU/qkmlwuJzo6GltbWwwNH4vAZ2dnk5KSgr29fanXlZiYiEKh0Mq9qFAoNHkai/srKCjA0NCwXM3RxMREmjdvjrGxcZl1RNSII8KGRvBRpJldQPCtuK5ICWS3/IkzGoGt9R8YKAvVKaz2TYI5R8CkfDFmkZLoSHTYMGwDQ2yGcOTBEUIz1FNyPSx74N7Vneftnq/UOuI/KcsxlceTmeGrI7Hs+fPnWb16NRs3btQq19PTqzCZrr6+fql5AC0sLLCwsCjzPGtr6xJlenp6JfIDmpiYlNt/WW2JlE6NjQjv3btHVFQU/fr1K7GYq1Ao8Pd/nDy2VatWmtxaN27cICsri5EjR2r+2RkZGVy7do1OnTrRp0+fCvtutCNCpRy2dCPiTk9kIRE1Z1gTwGDCADq1OIOu8u9MFW0cYeEZMC4/N9zT0thGhI2ZvLw8CgsLsbKyqmtTRGqYGgmWWblyJR988AEhISGMGTOGW7duaR2PiIhgwYIF7Nixgx07dnDz5k0AVqxYwcaNG7ly5QrDhg2jqKiI5ORkBg0ahLe3N6+//jo//vhjTZjcMIi8TBZWyEJFJZmnRXbGmwj5ZFTFU3bJwXBgmjqtlYgI6owQohNsGtTI1Oju3buJiYnByMgIGxsb9u/fz5AhQzTHw8PDmTt3LitXrtSU5eTkcPDgQaKjo9HX12fevHmcOXOGsLAw5s6dy3//+19SUlIYPHgwr7zySk2YXf8JOoo0xx4Ev7q2pFGg/O0OD+dMpZtCvWmaRz5w5P9g1gHQEVcNRESaCjUyIvT29sbIyAiVSsWVK1fo3r271vHw8HBOnTrFwIEDeeGFF4iMjCQoKIhevXqhr68PgJOTEyEhIdy7d4+BAwcC0Lp1awoLC8sVz220KAoh7DTSv5rgtdcUgoDq4J9EGL/wuOzB73C6GvZdqZQgzYL8NMiMhrSHkN5Ip7MFgWxPT6JnziKsz7OE9XmW6JmzyPb0rNGArvz8fI0cWnXzb0W4a6vf1NRUEhMTa9iapkONPPba2toSEBDAG2+8wXPPPceyZcu0jtvb2/P+++8zefJkDh06xIIFC1i7di0GBgaaOvr6+uTm5lJYWFiiXCaTYWpqCqjXFIunVp+kpr4g1U1l7TSNvYi+0IKi4KcPCRd5ApUK2b57BM0cRS/VRXWZ714y5YZk9nm10s2YR3jRwu97dBQF6MjySq0j6Bmh94InDeSjWTlUKuJXvE/O6dNaxVJ/f6T+/uTduEm7Lz6HMqIrn4aQkBA+//xzfvvtt2pve9KkSURHR1eq7ueff8706dMrDKCpSr+7du2iV69emkHAP7l69SrZ2dksXrz4qfsUqSFHePDgQb777ju+//57nn322RLHnZycNBFN7u7uvPHGG1hbWxMTE6Opk5iYiL29PYmJiZpyhUJBUVERzZs/DmhwdnbG2dlZq/3Nmzc3iGCAKgUt+HxCUmFvUInTotWOUoneb+EEL5iKY55aILpFwA5atLOD5yqYhs+KhZNvQsSlCruRKApp6bsV04VHqsPqf011PiRmHT1Wwgk+Sc7p05gOGkTz6ZXfSyiXy7lw4QISiQRXV1fN9gMfHx+io6NxdnbWUmUpPufy5csUFRXh4uKChYUFKSkpSCQSgoODGThwYKmRltHR0VhYWHDr1i2sra3p27ev5tijR4/w9vZmwIABGlWbhIQEbt26RefOnenXrx+pqamcPn2adu3a0alTJ+RyORcvXkSlUjFmzBh0dHQICgrSBPllZ2eTnp5Oly5diIqKwtvbm169emmUYEC9THT+/HkyMjJ45pln0NPT48qVKxQUFDBs2DBatGjB8OHDNYo7eXl5XLhwATMzM0aOHFnmlg6Rsqn2OyaTyVi5ciUbN25EpVLh6+tLTEwM+fn57NmzB1AHxezYsQOlUsmuXbtwdXWle/fuqFQqLl++TEJCAl5eXkyYMIEpU6awf/9+srOz+fnnn3Fzc6uyZFODpygPHp5H+qCwri1ptAhyOTq7fQjTn/Y4gOb3VRByoowTBPDdA9sGV8oJFmMa/UeV6td3so5UPBqrTJ0nKU10e+PGjaxfv56YmBjGjh1bYgpxypQpXL16FT8/PwYNGoRCoeDXX39l7NixbNu2TZNF4p+sXbuW8ePH4+vryxtvvMH3338PQGZmJu+88w6BgYG4uLiQk5NDYGCgRkz7k08+YcOGDcTHx5Oamsqff/6JXC7Hzc2N69evc/PmTUaMGIFKpWLmzJmah48vv/ySkydPcuXKFWbNmkVCQgLLly9n165dGpvS09OJi4sjICCAgoICXnrpJc6fP09AQACDBg1CKpVy5MgRdu7cSUFBAc7Ozvj5+bF7927eeuutKt1rETXVPiJMT09n0KBBmg8UwMiRI5k+fTo//fQTCxcu5Ouvv2bVqlUcPHiQ3r178+OPPyKRSDhw4AArVqxAKpXy+eefY2Njg42NDQEBAYwePZru3bvz9ddfV7fJ9Z+/zpCn14qiwAd1bUnjRqlE+OUOD2e+iIPOcXRUCjj2HzC1go5DH9dLDQOv1yHucbqfIgMT/mo3BD1UKHRUGMmlKFCiryxEolRgJC/ErCiX5nnpcG41vHK9UQTkFD2oWHS76OHTiW7LZDK2b99OeHg4enp6tG3blu+++44lS5ZozlmwYAFTp04lNjaW/fv3axLUDh06VCNkXRb/93//x9KlS1m6dClDhw5l+fLlyOVy9u7di7GxMf7+/gQFBbF9+3bWrVvHhAkTWL58OTY2NqxatQoHBwcWLlzIhQsX6NixIxs2bABg1qxZnDt3jnnz5nHkyBHef/99jh07xsWLF5k9ezbbt2+nT58+zJw5ExcXFxYtWgSgGW26urpiaWnJ9OnTefHFF4mLi+Pw4cNaWSsOHTrEoEGDWLt2LUVFRXz77bdVutciaqr9m2htbY2Hh0eJ8oKCAsaNGweog1527txZoo6TkxPnz58vUb5y5UqtCNMmR9AR8qW9EZTitGiNIwioDt/i4YtT6GxyCgNFIRycCf93Flr3gFvfwZUNoCjSnBLefChF4e24HpJOofzvfYkUr2v/rephboh5K3PmWVzCOCUEvH+ueNq1IVCZ2Zl/Ibr9zTff8P777+Pi4oK1tTXW1tbo6al/rjp16qRJjwTqaVFPT0+2b99O7969tdr65x7m0ije+N6mTRtNHsBWrVppFFmKRbifFNM2NDTEwsKCgoLH222io6M1x0Ht0NLS0pg7dy6zZs1i7Nix2Nvb06pVK622rK2tNemc/olSqeT06dP8+OOP9OrVq4TG6JMC24aGhmLKpX9JrT2SGhoasnr16trqrvEgzYSIy0jDh9e1JU0K1bFbRLuNo33bC5gU5cKB6WBiqd5v+DcpzXuQkeQIO73Jen4gU9suQpALIAGJoQ6CBNADQUdA0BEo0i0kSCJlQOHvcHkD9HJXjzYbMIYO9kj9y9caNayEVmgxT4puq1Qqhg8fTn5+PgkJCRQUFGBiYoK3tzdOTk6ac/z8/EhLS+PixYsUFRVx5EjV1mCDgoIYOXIkYWFhmrXA0pZfisW0i2MXDA0NNUF7oA4C/PnnnzXv7969y/Tp0+nUqRMmJiZ8/vnnLFy4UKutIUOG4O/vT7du3Uq1LTQ0lPDwcG7evIlcLtdK+wRqge3iYMG4uDiWL1+Ol5dXla5fpBYdYXmaeCLlEOJFvr4Vhf7itGhtozx3l0cuI7C2/xPz3ETIVYer5xk1J0HlCh4PEDJuoewzFNM2z6JKepzNQihUarUlAYzQJ73ZQHKb+WOekwiXPoVJ39TmJVU7zWfMqNARNp8xvdLtlSa63aNHD9asWcPw4cPp0aMHkZGRHD9+nKioKAC6d+9OUlISs2fPprCwEAcHB/bt24e5uXml+vz111+5desWAQEBfPXVV2XWW7VqFe7u7pw+fZqAgABN8t9evXrx6quvcv36dX766SdeeOEFioqK6N69uyb4Zt68eaxatYq9e/cCsG7dOhYtWkTfvn3x9/fnhx9+0OqrV69erFmzhhMnTmjWCQsLC+nSpQv79u3TSK7NnDmTX375hWnTphEbGysONv4louh2HVKpqNG9k0iONiXjkH/59URqDL3nemPVKxCLgiQim7uiuqZEGax+MBF0dUmc+TLdGUhw+xRkKNBBgoGgh65EBz2VLroqCToqHUyL9GmWp096m730feQBEh1YcgHa9avV66lWiTWVioSVq8guYxRi8cJkbDZuLHX7RFVFt7Ozs8nIyKBTp04lRmwymYzExEQ6duyIXC4nPz9fK7rcx8eHrKwsrXOaNWvGtm3bWLBgAd27d8fMzAwzs/LF1xUKBVFRUXTo0AEjo8dZS3JycmjWrBmgHpkZGxtXqEojk8mIiYmhU6dOmv3TT1LcplwuJyEhAVtbW5RKJbm5uVp5EAGSkpKwsLAQBbb/JQ1/tb4xk5cMMTeRRo2pa0uaNIo/A0mTdiPZqh/C4Xtam8QL3ObRurk9aUi5FVv+Gq6uri7uOkOQ5TuTY+lNs4wo+H0lLDpf5XW0eoOODjabN2E6dChZHh4UhoQAYNSzJ81nzMBi8qR/dW2liW6XJ1htYGCgOUdfX1/LCVaGf27HKIvinIT/pNgJAlqZI8rDwMCg1Lb+2aa+vr7m2vT09Eo4Qai8/SKlIzrC+kywJwUGVhT6/VXXljR5FAEl/wcqi5akWFnhlNGCc21CKmxDqVTiaxnLyMzuhLQewiCi1JGnAYfB6aWaMLt2kEiweGEyFi9MrtJpo0ePriGDStK/f/9Syx0dHbXSJIk0TcSdl/WZoKPkyZwQiooqritS62ROWEons3Ykt5ISm/yoUudEpMWSaVyIgXQUaW2fURf+8V8ozKlBS0XKwtTUVBONKtJ0ER1hfSXtAcR5UxAl/ovqIwo7JzINVVikN8NXUvl9coIgcL9ZHG0yrQkU/lYxyUuBa1/UkKUiIiIVIf7K1lfubENq1JKi+xVvWBapfZKGzaGbSTsSrPOJT6ma+PHD+EhSrQpprXAjud3fWpJ/blM//DREBAi7nciRzT5sf/0K21+/wpHNPoTdToQaDMUTRber9rmLiIgoU2GnqSM6wvqINAsCDpOneBaVVFrX1oj8g4KhU5GSiUmaMT7yf/eg4q3zEIuUZgQW9VNLuinlcGZFNVta8wiCwPldwVzcG0pyVA4KuQqFXEVyVA4X94ZyfldwiU3g1UVISEiNRYdPmjSp0nU///xzzVaO6up3165d3L17t8x6V69e5cyZM1Vq+5133ilVSPzVVysvLt9YER1hfcRnF8gKKIgpGVItUsfo6ZPYbSQ9zToQ1z6f5PSUf9VMfEoiiTZSOgljSewwTF0YeQUe/lF9ttYCoTcTeeidXObxh97JhN6s2shFLpdz9uxZfv/9d4qeWB/38fHhyJEjGvm0f55z/vx5Tp48SXZ2NgApKSmkpqZqBKtLIzo6mszMTE6fPs29e/e0jj169AhPT08ePXq8/puQkMCRI0fw9fUF0Ihu37p1C0EQkMlknD17ltOnTyOTyVAoFNy/f19zfnZ2tmYUGxUVhYeHByEh2oFWxaLb165do7CwEIVCwYULF/Dy8iIzMxOA4cOHM2HCBEAtun38+HEuXLiASqUq997m5eVx6tQpAgLUez9jY2M5duwYISEhZGdnExsbi5+fH+fOnUOpVOLn58fFixdRKpXlttvQER1hfUMpB++fKDRsQaGfOC1a30if9A6oHmGYrI+PNOyp2rojC8Uw2YDg3GdQ6P4tyXbxExDK/zGrT4TcTKiWOk8iim7XnOj2W2+9RWBgIC+//DJ79+4lNDSUoqIibt++za1bt3B1dWXPnj189dVXDB06lJ07d/Lll1+yfv36Kv0PGxpiuFR9I+Q45CSQreuGKq9u1ilESkdl2ZbU5p3pYwIxLXNJj894qvbSMzOI7ZhH10I3Yts/pEvM75AUBAEe4DSrmqyuWTISKk4UXZk6TyKKbtec6Pann36qSYIwa9YsfHx8MDc3Z/HixZw9e5YePXrw9ddfc/XqVT755BO+++47goKCePfdd6v0P2xoiCPC+sadbQAUPGx0gj8NnkfjVmBAFHopOvjkVc/ezj9zgpGkCERmP0uR0d+SYJfXaYl6N3iquJ/+xIkTeHl54eTkxJ49e4iPjy8hup2amqqpXyy6PW7cuBKOoL6Ibh87dkyjU/pvRLfHjh3Ll19++dSi28Vaqra2tppp1tKOGxoa0rJlSwB0dHQ096WxIjrC+kTsbYj3JdukM0W+oXVtjcgTqCxakqtviqOJPREdc8jKzqr4pEqQk5tLZOccugvDiWwzQl2YFQfeP1VL+zWNpY1pxXWsK65TzJOi2yEhIYSGhmqJbgPlim5v3rwZaRUDzIKCggAqLboNlCm6/eR64N27d3FycipXdBuolOj2pUuX2LJli9aaKahFt0ND1b8VcXFxTJ5cvqiBt7c3oF5vffIeFjvYJpfr9W8qPTWqUqlIT09HLpdrnpSMjY219PZEnpK/R4P5Ob0QlL51bIzIk8gc+mOmE4UkpQv3mj/d2uA/uZsSTKfCwSQL/ehschOjggy4vgWenQ9GzSpuoA5xHNaO5KjyxQAch7WrdHui6DaaNmtCdHvfvn14enry8OFDDhw4AEDv3r15+eWXmTZtWqXuV2OkUqLbSUlJuLq6Eham/QOwfv16Pvzwwxoz7t/SIEW3s+Lgmz4IKiWRvoORPYyuU9tEtMl//mVad3iOh+YZXI+t/oeU52z78ExGW3JbbKN73HF14bB3YNTH1d5XdYpuC4LAxT2h/PVnyUhOgG7PtWXUwh6ljjRE0e2aEd2+ffs2+fna67KWlpb07dsXQRCIi4vDxsZGM9WsUqmQSqVao9umRqVGhAcPHiQiIoIVK1Zo5o0BXFxcasywJsef20ClIM28v+gE6yEKi5YIGSruFVXvaLCYe4nBOAgtSM1/jk7GVzCSZqlnCPovAYvKj6hqG4lEwuiFPenQ05Lg6wmkxanXuqw6mOM4zIZuA9tWeY0QRNHtJ9usTtFtiUSCra2tVpmOjk6TdoJQSUdoZ2eHra0tmzdvbrJzyDVKUR747Vf/GW8DVC3cXKQWMLUirHkG+bFVi4CsLHK5nCDbFPpn9iWu1TAcYk+CXArXNtf/nIUS9civ23NVy4Agim7XDIMHD65rExoclQqWef7557G0tGTQoEHMmDFD8/L09Kxp+5oGfvuhMAeFrgkFd6tHoUKkelEaNuNecsUZJp6GwPgwCuRFJOYNpMjw7yd0v18gRQycqilE0W0RqKQj3L17N97e3oSFheHr66t5labwIFJFBBXc3Q5Aht5zKNPS69ggkX+ibGePykCnRMRetfejVBLSOpkuioE8Ko4gVSnh0roa7VdEpKlTqUeh3NxcOnToQERERKmLuv8kPDycdevWERkZiYuLC//9738xMDDQHBcEgU2bNvHHH3/Qu3dvNmzYgKmpKeHh4Xz00UdkZmayfPlyTSjwTz/9xK+//krHjh3ZtGkTrVq1+peXWw8JOw0Z6lFgQaSYXbo+UmT3LArd2tF8DYz/C0e9NiTkPUsH/UsYyKUQdgpi74DtoFqxocoIAsFXL+J/4XdSY9QKKq06dsFp9Dgch48qMzFvSopanq5169Za5WFhYdjZ2VXqt0ZEpDqo1Ihw4sSJ6Onp4eHhwYULFzSv0gRcAebPn8/zzz/P6dOniYyM1MgWFbN37168vb3x8PDA3NyctWvXAjB9+nTmzp3Ljh07eP/994mOjubSpUvs2rWLAwcO0L9/f1577bWnu+L6xt9bJqSGbSj0fhyIIZi3QGUpZp2uD0hb2SPXrZm1wX+iVCoJa5NKF9VQ4q2fCEY7/xHUkHj10yAIAqe//R+/b/uKxIdhKGQyFDIZiQ/D+H3bV5z+9n9lim57eHhw+PDhEuUbNmwoEeEpIlKTVMoR3rlzh6ioKObOncuYMWM0r4MHD5Za38bGBnd3d8zNzRk1ahQPHminlzly5AhvvPEGVlZWvPbaaxw/fpzwcHVOt+eff56OHTsyZcoUzpw5w9GjR3nllVdo06YNL7/8cqWEZRsKhhlhEHMTgCxZf4Qn9BBjJ/+X+yM+RWnbtazTRWqJIlML8pS1l77GPyGMojw5cfn9Uej+HcjxyBsenK01GypL0OXzhN28WubxsJtXCbp8vtw2rly5wsWLFzXf6w8//FAT9RkREYGHhwd//aVW8hEEgaCgIOLj4zl+/DhZWVnExcVx5swZLefp7+/P0aNHefjwsV5vUlISx44d0whml1Um0vSolCMcM2YMf/zxR4nX7NmzS61/5MgRQK2ssGXLFo2aQjGxsbGaEN42bdqQkpKiVQZqZ5qYmKhVrqenR7NmzRrN06JFyC+av6XBj6Wackb/Hwk5phRIVdx79j3kPevplFgTQWloRrYsr9b6UygU/GWTTidhKPHtnxgV/vFfUClqzY7KEHixfCdXUZ1vvvmG8+fPs3PnTubPnw+oZ5RSU1P5/fffmTdvHgkJCSxZsoRDhw6hUqkYNmwYK1eu5NKlSwwZMoS3336b8+fPa1IY7d69m1WrVhEbG8usWbO4du0aSUlJuLm5ERMTw6effsr3339faplI06RSa4RVzSdWUFDAihUr+Ouvvzh+/LiW/h6o1SOKtfVkMhlGRkYYGRmRk/NYoaJ4g+eTdQEKCwsxMTHRvL9x4wY3b94sYUNNJeysLnQLUrGNVv9AJBs4UBSoHjUXWnch0GAAOsJlTJp1ICu5I3/aLuAZPROaBVyqS5ObJIKuHlK5Dmk5TyewXVXuJ4TQVWFJeJED7XQuo6dSQNpD0s5/SU7X+qMAkhYXU3GdR2XXcXd3Z8OGDQiCgIODA+npj4PFPvvsM/bs2UPXrl2ZNGkSL774IjNmzEChUPDzzz9jYGCAubk5vr6+GBsbazacd+nShd27dwPw4MED7t27h4GBATo6OowaNYolS5YQFRVFdHR0iTKRpkmlHOG5c+c0yuhPUpayzLx58xg5cmSZT1iOjo4EBwfj5OREYGAgffr0oWvXrkRGRqJQKNDT0yMwMJC5c+dSVFREcHAwkydPJikpiZYtW2opOjg7O+Ps7KzV/ubNm6tNOaPGOPMDqOQAKLK7g+CLoKtL1Ij3MSeMgZbDyVVmEqJnQHq8DH/rGfRt3grTa7/WXbBPaAAAIABJREFUseFNC4XDszRvZkJBaun57GoKuUJBhG0WPfMmktQyjPax6ocgq/vfYjV0Hpj/+/Xjan1IrMS24vL2Hj+p7dmhQwctIei4uDjs7e0B9Qb7YifZqlUrzd6/5s2bayQfBUFAqVTy8OFD3nvvPXr16kVmZiZdu3Zl0KBBfPDBB6xatYro6Gg++OAD5s+fX6LsmWee+Ve3QaRhUylH6OrqioeHh+b9o0eP2LBhQ6kbYtPS0rhw4QJWVlYsXboUUKdCGTt2LOPHj8fPz4/ly5fz0ksvERsbi4eHB59//jlWVlaMHTuWl156CQcHByIjIxk1ahQ9e/bE1dUVlUrFuXPnWLGi4WXxLkFigDr5LqDS0afgvjqxacq0NQiGqfQybo9+vA4t9VthpOeDrp4T8iIlPgYjeNatGc3ONQxB5sZAoe0zSAzlNZZlvTzup4TRXTaUcF0nbCRX0BFUUJgNZ1fAjP21bk9pWLXvSGJ4+Zk4WrYvqRJTTLEItFQqJT4+Xmt5pHPnzgQEBNCnTx+8vb3p3bs3ULEw9Lp167h//z7Nmzdn2bJlAFy+fBldXV1Onz5NYmIibm5udOjQoURZ8fSsSNOiUo6wU6dOJdKZXLhwgVOnTjFw4ECtclNTUy5d0p7Cs7KywtLSklGjRgHQr18/Tp8+zc2bN9m/fz+Ojo4A/Pjjj5w9e5b8/HxWr16Nvr4+tra2XLt2jT/++IMtW7YwYMCAf3ut9QNBgDPvqveHARmGA1HERCEdMJ5MM0vaquKwSGpDYsdCjGR69GMA3kYZJEaZoFSo8FH24ZkXV2J1bFMdX0jTIL9FR9Ct3dFgMYWFhfw/e+cdHmWV/fHPzKQnk0IaSSAQQhIMvUoJHaUXYUEQbKviImtDUX/rrmtBRVxZlV3LKruCuiIgoEgT6Ym0BAKhJqT3nsxkMpOpvz9mMzCQMoEkk8D9PE+eJ3nfO/eeeTPznvfee873pISWEaEaR0HnBIKzDptPXPgJLm6Hu6bbxa5r6TNhUqOOsM/4ifWeS05OZtq0aeTl5fHnP//ZKs3q3Xff5eGHH7YIU3/55Zc22TRt2jRmz56Nj48PHh4e/Pe//2Xu3Lk8//zz7Nu3j0uXLvHYY49x1113MWnSJKtjgjsTm0S34+PjLQEwYBa/XbduHcuXL7ekPjSGUqnkwIEDjZYJaQ7atOj26a/hx6spIFkl01HGZ5E++zVkqkT6GIZR4avjR/VveMu9mF7QmyzvdFIrwlGWXq0JdlfHCoK+/0u7qmbeHrmy8B84hCo4nn7GLuO7ubpxv3o46f67GV38DyT87+sq7whLT4BL3dqbDdHcotu7/rmai0cO1Hk+etQ4Jj31fIOzuKKiItzc3OoUvNZoNGRnZxMWFtYkBZjMzEw6duyIs7MzxcXF+Pv7o9PpSElJISAgwCKIXdcxwZ2HTZ+spKQk3nvvPatj/fr14+GHH7Z5ILlc3ipOsE2jroBfrz44qGUeaI4nUzT7T2hKjzDMfRIaJx17DOaq3EWlxVzuVkF0XiQFzokoJVHU3gcvFnjjPvlJPHd+aqc3c2eglThSo2+91InrqVZXk9q5gq7V4ykOSSAg9zfzCWUB/Po6TPu73WwD8zLllKXL6NqnP2f37aYo3bz/GBDWjT7jJxE9cmy9CfW1XJ9Qfy0uLi4NClPXx7Wi3bUCHI6OjpYitrXUdUxw52GTI1y4cCGzZs2y/O3p6YlMJmsxo25b9r8FqquVtQs1/VHGjCSvLIExvlPRqrX84nMORenVKNnjBUl0dhpBX/ce4GSiIONqd2U+UbTtanXtG5O7FxJHR8prWi91oi5OlV2ke9VQLgb2I4Dfrp6I/w/0vA/C7FwFRiIhetQ4okeNs68dAsFNYlMeoZOTE5s3byYhIYHjx4/Tv39/Fi1aRFWVfW8Q7Yr8s5DwH6tDlZUhXHaqYnTIFAwKHb91yqCwtMiqjU6n47h3Oi65Dsj1l3F2u/rsUlLthqDl0EYNxsNVSoXKvnmrVSoV6aFKgo0TKAi5NqfUBDuWgR1nrALB7YBNjnD37t0sXryY/Px8nnjiCUpLS9mxYwefffZZS9t3e3BdgAxAlXtXUmRuDOt0DxToORVeQEpu3WHtafmZZHetppdTf3z8cyzHFeU6DMHhLW7+nYo6+C5cnMyOyN6cqriEa7EzidV90cuuBpRQkmKuZi8QCG4amyXWpk6dSs+ePcnJyeHNN9/k97//PWfO2CeAoN2R+A1kn7D8aUJCvMcwwkNicMyVcDmigsTs8w12Eac4S021lig3D/xCrt4Iq3uObjGz73RU8k5IHFu24oStVCoVZHSuIkI6hbTQe6xPxv4dChv+/LQoJlAlFFL0SSK5f4kj9y9xFH2SiCqh0LKnXRdlZWXk5uY2ebjS0tJbrnyTnJyMVqttvKENJCUlNUs/rY1Wq7WSoLuTsckRyuVyMjIy+PTTT5FKpYwYMYLExESrqsyCerguQAbgTLcZuFaNwL8sgMIwLXG5pxvtpkqlIrFzPj4lvriYTiFzNP/rFH5RLWK2ABR4oZPaJ3WiLuIVl3AqkJFW0JcqeeDVEwYd/PS01YpDq2GCsg2XKN+UjDZLiUlnxKQzos1SUr4pmbINl+p1hrt27eKTTz5p8pDbt2/nq6++uiWzFy9eTF5e0wpgL1++vM7toFdeeaVd6h8XFRVZ8ixt5fLly3z44YctZJH9sMkRPvDAA5SWlvLll18ybdo0YmNjOXjwIHPnzm1p+9o/1wXI5HcaTMaVcDpVdqPIV83ukmM2f4nOZF+k1L+GAV6DCehslqMr0Xu3iNkCUFZL0UjtvyxaS4WigsyuVfR2HM05zzHWJ3MT4GTrCy2o4guoPlNc7/nqM8Wo4huevcXFxbFnzx40Gg2VlZUWAX4wq8uUlJQAkJiYyLFjV78vKpWKjIwMzp49S3Z2NgBHjhxhy5YtVgo1KpWKPXv21LuCVVhYyI4dO6yq6RgMBn755Re2bdtmSfb/8ccfSUxMpLq6mvT0dJKSksjKymLlypVIpeZb6blz59iwYYPFnrpQq9WkpqZy4cIFfv75Z4tzzc7OtthdVVVlkXw7d+4c+fn5bNu2zTKL3rFjB2VlZtm/lJQUysvL+emnn7hw4WrxaJPJRGxsLIcPH7aa/WZlZbF//35UNiz5JyUlsWXLFrKysgDz6uDOnTvJz88HzI5x48aNpKamAmA0Grl06RIZGRmcP29epYiPj2fLli1WEnbV1dX8+uuvpKWlkZycjMFgfojLy8vj559/Jicnh9bEJkcYFBTEhQsXOHToEBs2bGDYsGH89ttvjBkzptUNbldcFyCj9O7Moay7GOxyL9UeBvYaTqPT6ZrU5WHTeSjSESxVIvd1oqzUgEneobktv+MxBHZB5iShqo0FohyrOIdOoQXlKAqDBlqf3PcGlDeu/dmcqE40vkTZUJsNGzbwww8/8N///pclS5ag0WiYMGGCxdktWLCA3Nxc3nrrLV555RW2b99uSeW6cOECU6ZMYfny5RQVFbF06VLWrl1LSkoKMTEx5OXlUVFRwdixYzl69Chvv/32DfnFp06dYvr06Zw9e5YHH3zQoqA1Z84ctmzZwrFjx5g4cSJXrlxBqVRy9OhRLl26xNSpU3nxxRcpLCxk6tSpGI1G1q9fzx/+8AdycnIYP358vVJ2qampjB49mvfee48jR44wfPhwNBoNq1evZu/evYDZ6f/5z38GYPTo0SxfvpzDhw8zfPhwnnnmGfbv38/kyZMBeOaZZ5gzZ47lPWzatMly7b777ju2b9/Ovffei06n48CBA0yfPp0jR47whz/8ocH/27Zt23juuefIyclh9uzZJCUlkZiYSGFhIWlpaWzevJnFixeTm5vLwoUL2b59O2q1mnvvvZfHHnuMtLQ0PvroI95++20yMjKYOXMmCQkJVFdXM2rUKHbt2sXLL7/MqFGjUCqVxMbGWsaZN28eO3bsaNC+5sTmDFUfHx9GjTKHadcqwYBZPX7VqlXNb1l757oAGa2TG/u0IxjhuwB9sY59Hc+jLml6sdeS8lIuhZcTndONIt9qlKUS1H3H4Ba7pbnfwR1NTfcBeHjKKNIoG2/cilSpVCSFFjMgO5yz9GG89AzS2ooU2mpz4MyMj1vNHl1h40vHDbUZNmwYq1evprq6mt69exMYGEh0dDRHjx6la9euKJVKIiMjWbt2LcnJyTg5OVmpz7i5ubFnzx5yc3OJi4sjMTHRcm7t2rU4Oztz//3388ILL1iEvV977TVLmxUrVrB69WpiYmJ48MEHmTVrFt27d7fMwAA++OAD7r77bgICAnjsscfIyMjAxcWFPXv2WL2XN954g4MHD9K5c2f69OlDaWlpvcIF7u7ufPXVV0gkEvLz89m1q/4SWzU1NXzxxRe4urry73//m+PHj+Pl5UV4eDhqtfke8uyzzzJz5kxmzJjBkiVLCA0NRaVSWeo9Pvjggxw8eJBVq1axdu1aBg0axPjx4xsURElMTCQsLIx58+YxY8YMnJyc+N3vfkd+fj4jRoygT58+7Nmzh6CgIMaMGcMzzzzDuHHjUKlU/Pzzz7i6urJ3714eeughNBoNp0+f5syZMyQlJTFixAg++OADDAaDRbXs9ddf51//+hd9+vRh1qxZLF26lKlTp9ZrX3Niu1SDoGmc/toqQCY+YBp3Vc9GkmfgZGQeBVmFN9318bwkOrvEEODiQTYqlMF9cUM4wuZEHRiJ3EXGZWWlvU25gdM55wl370BXp+mkd84jPPOaG3JN27O3IWHuWm1RNzc3y0194cKFbN68mbCwMBYuXEhBQQEBAQEWBxgWFmbZ3wsLCwPMy33XJt537dqVuLg4tFotZ8+e5fjx4wAMGDDAMg6YVXZWrlxpqWgzcOBAMjMzrZLsX3jhhRvsvl5y0mQyUVZWRufOnQG49957G7wk3bt3t6jtdOvWzWopF8yKOrX4+vpahMU9PDzw8jKrCUmlUsuKUu17DwsLo6KigvT0dC5evMi8efMs/Tg7O5Oenm7VtiGWL1/Oxx9/zKxZs3BwcLihiEJZWRlBQUGW61FcbF4i79ixo8XeCxcu8Oqrr9K7d29KSkowmUxkZ2cTFWWObZDJZHTsaBaQT0tL469//SuOjo4ArSqAbtPSqKCJFF8yVxT/H0ndpqEtHoR7vhspEQrOZV1q4MWNo9fr+U1+Bc//yauVyQIbeYWgqVS5dsTRyYBa0/RZe0tjNBo56n4FlzwnLhf3otrD1262OAY2nsvaUJu6pNdmzZrFnj17+OGHH1i4cCFBQUHk5eVZ9tLqKqLbtWtXLly4YNlrOnnyJH379iUiIoKJEyeyceNGvv32W4vucS0RERE8/fTTbNy4kffff5+QkBAiIiK4dMn8HdXpdIwaNYqamoajhyUSCcHBwZa9tFdffbXBWd6lS5csTiwhIYGoqCg8PDwspeji4+MbvEbXc+7cOau+IiIi6Ny5Mxs3bmTjxo3079+f4OBgIiIiOH3aHJx36tSpBvv8/PPP+d3vfsexY8f4/e9/bynEXqvKGRAQYFn+PXHiBH379r2hj7fffpsjR46wdu1afH3Nn9OwsDDLXmZRUREXL14EzP+Ll156iY0bN/Lmm28SEhLS6PtuLsSMsLmpLoXv5purBAB5nQZxKTmM4dLelARriM1r+MNnK1mFOUSHdsLByZXiUujh5IJE27b2s9ozlTo3XB2bJ7y+JcguzCW3Sxf6qu/lgkcmg6o2N/6iFsD97iC02Q0vH7sPCWpan+7uDBo0iJKSEsvN8LXXXiMmJoaoqCgUCoVlJlJLUFAQ8+fPZ8yYMXTq1InS0lJWrFiBXq9n6tSpJCcnk5aWxsKFCy2BLQBvvvkmixYt4rvvvuPMmTN8+OGH9OrVi6FDhzJ+/HgMBgOTJ0/G2dmZ3r178/jjj1v27q5n9erVTJ8+nR49elBaWlpvu1qmTJmCg4MDHh4eDB8+HCcnJ+bNm8e2bdtwcHDA3d3d5mv22WefsXXrVhITE/n6668ZOHAgvXr1YtKkSZa6jS+//DIrVqxg0aJFDB48uNH4hKioKObPn8+QIUM4efIkn376qaUIwqZNm1i1ahX33XcfAwYM4OzZs3zzzTc39DFp0iRmzpyJm5sbrq6ufP311/zyyy9s2rSJSZMmIZPJ8Pb2RiqVsnLlSh577DH69OlDYmIi//rXv2x+/7eKTaLbDfHSSy+1uT1Cu4lu69SwbjrkmEvLVHoHs6N8LKPdH0KtreFHl5Mom1GNZ3BoHxTZgZTl1zBCsRXnU782W993MiaZjNgJ/yS8v4ojGScaf4Gd8PSQM1sxhFyvK0S6r8W/IAl6zoK56xp8XXOKbmOCso2XqT5dVOdptwEBdJgbZVPdwmt54YUXmDhxotUSY0lJCRKJxDKzqIuSkhLUarVliRLMM5j09HS8vb2tZoO16HQ60tPTCQkJsXI+ZWVlSKVSvL29Lf2oVKo6xcFrqampsTjw4uLiOiNVnZ2dWbVqFZs3b6aoqMjK1pqaGiorKxvUX72eyZMn8/e//x25XE6HDh0sy5IABQUF6HQ6qzHUajXFxcWWZemLFy/ekM8pk8kYO3YslZWV5Obm0qVLF8u10Wg0SKVSnJycqK6uJi8vj7CwsDplN00mE5mZmYSEhODo6EhxcTE6nY68vDz69u2LRCKxlN2TSCRotVrS09MJDQ21eh8tzS3PCFvT2DaNyQQ//dHiBLUOzhwyjWKE3wMYC7QcDElGWdS8knSlukp8PTtSlg/KrgOFI2wm9GG9QQJqU9tJnagLRZWSi11L6Jvbg9NOA7mHc031N7eOBDrMi8IlwgfViXy0eeZr5hTsjvuQINz6BzTZCS5dupTz58/zt7/9zeq4LdUh6mojkUgadPyOjo5ERkbecPx6pymRSBp0gmB2crYu6Tk7O1s5qNpjTXGC11LXuLX7b9fi6upqVfexIby8vCx7krVcWxjdzc3NUjy5LiQSidV+qr+/P4WFhTz++OOMHj2as2fPsmTJEsvyr5OTk2X/sDWxeUaYmprKmTNnLGvwAL169eKuu+5qMeNuFrvMCH993azw8T9+6zIPL+VMvPK8OBmZx5msi80+pLubO8PcR3ImqZrQYBPd//vHxl8kaJSq8Q+T4j8Saad0LuVcafwFdkQmkzHXZSS41OAk/xfd3D1ad0bYAuTl5eHv728JmrjdMBgMqNXqRp2qrVRVVeHq6tquCiFotVouX75MQEAAgYH2j3GwaUZ46tQphg8ffsOG8dtvv90mHWGrk/itlRPM7DIOVV4vQlXeZIVXtYgTBFBVq3D2MYfOFysc6S6RivqEzYDKNwwPDxm5aoW9TWkUg8HAcc80JmRFckZ9F0GRZbT3NZrg4GB7m9CiyGSyZnOCQLP21Vo4OTnRu3dve5thwSZHuGfPHtzc3Ni0aZPVh7Q1o3qagrupFatipB+B7c9a/iz178GJ9EiGy4ZQ7qfhQNGNEW7NiVamRCJxQV2lRxfRH8fklh3vTkDp6Ie7i4RyhX2rTthKen4WeZ0606tmCqd1Jxlub4MEgnaGTY4wPDycgIAApk2bZlMor71ZovknbMqCgY9CtzEtN1BJCmxcZNZ6BDTOHhysGsBwz/vQaLT8YjzVZOWYpqKSaPHoIEdZqkUVOQxv4QhvmUq1E96BxmYTZW4N4jTnmV06kIDO/Vt9bJPJxJkzZ4iPj6ew0JwfGxgYyKBBgywBEW2FpKQku8xELly4gFwuR6PR0LlzZ6t9NltQqVQUFxffkL/YEqSmphISEmJlo8Fg4PLly7dUxLiiogKVStUiE6js7GzkcrklsKmp2JRH2L17d6qqqhg+fDiLFy/mySef5Mknn2wwT8aeyDDA+W2wfiZ8PgoSvjJHdDYn1WXw3f1mUe3/keA7lb5uczGU6Tjsl4KiquVVScoNVXh5m/+NlV6iJNOtYnSTo6jQY2rDqRN1UVFZwaVuZfho/Ft1XJPJxJYtW9i2bRs5OTnodDp0Oh05OTls27aNLVu2cIuB6YA50nHZsmW33M/06dNvuY+mcvr0ae677z6ysrL4+OOPb6pyxtmzZ3nzzTdbwLobWbZsmZXuKpgdcUMqNLZw+PBhPv64ZVSP3n//fQ4fPnzTr7fJEaakpFBdXc3ly5fZvHkzmzZtYtOmTZak0/pITU2tU1DaZDJRXl5u+amuvirBlJeXd0O/er2epKQki8hsk8g/Y166/LAX7HsTFE1TnK8TRR5seABKUy2HLoRNwVQxFJdcR853LyGzoH7R3eakSFWGl6v531hSbXvekaBu9JEDMRlNaCVtf3/wek7mn6PaTd+qY54+fbrBMkRJSUmWBO7rKSsrIz8/n7Nnz1pEt2s5duwYW7dutYhXX7x4kW3btpGWlkZBQQFFReZ0jZqaGpKTkwE4f/48paWlFhWZ5ORkNm/e3KQySVVVVezdu5fMzEwuXbpkceJJSUls3ryZy5cvW9oWFRWxdetWTpyoP8XGaDSyb98+evfuTUREBM888wwdO3YkLy+PsrIyfvnlFwwGAzqdjv3793P06FGre2ZycjKHDx9uNKEfID09ne+//96SoA6QkZHBpk2bLALYYE6+LywsZNu2bZSUlJCfn8+OHTsoLS21ug4///wzZ8+eBcy5nX/9618B83VWKpXs2rXL6nqo1Wr27t1LQkKC1cPP+fPniYuLQ69v/LOZnJzMhg0bSE1NRafTWcYHc/mtWsGCa9tdj1KpZPfu3RaRAVuwyRHef//9lJWV3fDz/PPP1/ua3NxcRo0aZfXhriU9PZ0+ffowb9485s2bx9q1awGzbum0adN45ZVXmDJlCgaDAaVSybBhw1ixYgWjRo3ixx9/tPnNWaEqMeswftgbvv0dxH1olkAz2LB0aTJBXiIcfNc8w1wdDVlHLacLg3pzIa0bYVU9KAit4UT22QY6a17KKspwdzR/cSrLdRiD2m40YHtAHRKNs7sD1bQ/cQKdTsdp6hZ6bikaUydpqM2uXbuYMGECX3zxBevXr+fJJ58EzEnuH3/8MampqUyaNInLly+TmJiISqUiKSmJ//znP3z//feAWVqttpTQnDlzePDBBzl16hR79+7l97//Pbm5uSxdutSiitIQCoWCmJgY9u7dy7Jlyxg5ciR6vZ5vv/2WF198kZycHBYtWsSvv/5KSUkJEyZMICMjg/fee4/Vq1fX2afBYODs2bMUFRWRlZXF008/TUZGBp999hkTJ05k/fr1aLVaJk+ezJ49e1i3bp1FFm3Dhg089NBD7N+/nxdffLFB2w8dOsTs2bPJyspiwYIFHDp0iCNHjjBv3jxycnJ4+umn+eILc3WScePGsWzZMuLi4hg+fDhPPfUUBw8e5J57rta5fO6550hKSuKJJ55g3bp1KBQK7r//fgDmzp3Lww8/TEJCApMnT+bChQtUV1czYcIEDh8+zEcffcSSJUsA+Oc//8nSpUvZs2ePlcZrXfz4448sWrSInJwcpk2bxvnz57nvvvsscnpvvPEG+/btu6HdtbmaxcXFjBs3jhMnTvCXv/yF119/vcExa7E5j/CLL77g/fffJysri4MHD/Kf//zHUp/wev7zn//wz3/+06I9dz1XrlzhiSeesLowarWa9957j0uXLiGXy5k5cyb79+/n0qVLjBo1ig8++IDU1FRmzpzJzJkzbTX7Rox6SNlr/gFwdIWgvhA6FDoPhS4jwMUT9BrIOgaXd8HFn+qdSVa7+3C4rC8j3KajMtawX3mqWZaCbMVkMmFwrKb2mUbVaxTy/Na9Gd5OqDxD8ZDIUGrbTh3CplCjb90l3dqZ2c22GTBgAGvWrEGtVlv27gYOHMiyZctQKBTExsZy7tw5fve73/HBBx8wc+ZMq1JD16LVavnHP/5Bt27diI+PZ926dXh7e6NQKIiPj+eBBx5o0M6vv/6aKVOm8M4776DVai17WaGhoXz11VfIZDLS0tI4deoUvr6+GI1Gxo4dyxNPPGFVOupaHB0due+++4iNjWXQoEFW56ZPn85rr73G5s2biYyMtFTVGDNmDJcuXeKNN97gwIEDdOzYkR49evDLL7/Ua/vKlSv529/+xvjx4xk/fjyFhYV8/PHHfPLJJwwaNIiFCxdy991388QTT1BTU8Pnn3+Oh4cH69at44svvsDPz48ePXpYJN7efPNNxo0bx9y5c5k/fz4zZsywjGUymVi5ciWRkZFoNBqOHz/OkSNHGD9+vGX5tk+fPhQWFrJq1SrOnTuHXC7H39+/wWpFK1as4Msvv6Rv377cfffdKBQKFixYwA8//MDSpUvZuXMnK1asYPz48VbtKiuv6ut+8sknPProozz11FMYjUa6devGn/70Jyuh9rqwyREeOnSIxYsXc++995KVlYVcLmfdunUMGTKExx577Ib2jz76KI8++mi9m6JXrlzh9OnTzJo1i/DwcF599VVSUlLo0aMHcrkcMKvSJyQkcObMGRYuXAiYg3ZKSkrQaDRN3myuF53a7PCyjpn/ljmCfw8ovdLovqJRIiXWfRKDDPMwFGg5FHKZ6qLWv4GqpWpcPbxQV+lR+PZA3uoW3D4o8ELu4UB6O0idaC80FCxTm1Du6upqWf47ffo0K1asoFevXigUigYfLK9fcaoNJsnLy+MPf/gDUVFRyGQym5Lxs7OzLelgTk5O+Pub91vT0tJYtmwZPXv2RKFQEBISQv/+/Xn99df5y1/+QmpqKi+88AL9+vVrdIy6bE1PTyc2NtYyEwwICMBgMFBSUmJJiG8sSCYzM9Ni+4ABAwCzOk+tUEBAQIBFbNzb29uScuHs7GxR6pHJZJYAsU6dOgHmh4DrBcGvPe/u7k51dbWlxmHttlaPHj0oKirC0dHRck/v2rVrg47w2vcwcuRIwJyAv2TJEvr378+gQYPw9PSss93mzWaJwbS0NH799VcOHjwIwJC1mIZ9AAAgAElEQVQhQ9BoNM3jCA8cOMDAgQPZtm0bPj4+9OzZk3nz5hEXF1enI2wMuVzOyJEjmT9/Pl999RWPPPIIzz77rFU+jJubG8XFxSiVyhuOq1QqiyOMjY0lLi7Oqv9bSqU36KDAtj2F4x0n4FY6FEeFlLjQDHKKmmH/8SbIV5XhLHdHXQUFNR60zaSW9kFphYlgdzXlqvaROnE9KpWq3jp4LUFAQECjNUlrHUpdXO8kjUYjH374IYWFhchkMqvgllqHWJ849bX87W9/49///jd9+vRh5cqVNs1crxWDzsnJsczy3n77bWJjYwkICOC5554DzPcdrVbL9u3bKS0tZcSIETd1LwSz2HS/fv1Yv349AC+++CLBwcEEBgZy5coVunfv3ugSdK1QeHBwMF988QU6nY7w8HASExMZNWoU58+fJzzcHExnSxTvyZMniYyMJD4+vk4x7ev7iIiIQKfTsXr1aoxGI08//TSRkZFotVqKi4vx9/e36T1cvHiRvn37smrVKjp37syCBQuorq5mzZo1PPTQQ/W2u7aPnj178tJLL1FTU8OyZcssjrghbHKEISEhZGRkcOTIEcC8Ufnbb78xf/58W15+Aw8++KDl9+XLlxMUFMRbb71l9YUqKSkhKCiInJwcy4Z5rdafj4+PpV1MTAwxMTHWA7z+zk3Z1RTyOg2iICeaIYYIssNUXMy/cdO2tahCTZiPKxX5apSVUkzyDkiUNxFYdIdj9O9EjdqE3MsZQ5Wh8Re0Qdzd3RtVjWlORzlw4MBGHeHAgQMbPH8tUqmUESNGMGvWLGQyGW5ubqxfv545c+ag1WotQs+TJk3i2LFj9a4MTZs2jccff5ywsDC8vb05cuQIr7zySoNjP/TQQ8yZM4fJkyfj4OCAj48PUqmUadOmMW/ePPz8/JDL5Rw5coRFixbx9NNPc+jQIVJSUm7aCQLMmDGDr7/+mtmzZ6NQKOjXrx8+Pj588MEHzJgxgwEDBtxw37ueWjHtXr16kZKSwk8//cSwYcN45JFHGDBgAGfOnGHNmjU227R+/Xq2bt1KSkoK3377baPtH3zwQaZPn878+fPJzc1lypQpODs78/777zNu3Dh69eqFUqm0qmV7Pe+//z4PPfQQ0dHRZGdnWwrzLliwgNWrV1vsqKvd0aPmmI0//vGPTJs2jaSkJJKTk3niiSdscvw2SaypVCqGDh1qFYXj5+fHmTNnGlSBCAkJISUlBTc3N2pqajh69Chjxoxh2rRpPPnkk0yfPp1du3bx4YcfsnPnTiIjI9mzZw8hISGMGDGCjRs3cvLkSbZu3cr333/Pzp07+eKLLywFM+vlda+Gz98CBpkjyaHDOJvRlZFOC1HIathq+M2mqK6WwtHRkXEdxnHqjHnpY6juV9zittrNnvaKethMjjrfS8+7TRzMPGJvc26Knj17Mnfu3AbbNKfEmslkYuvWrVbRfdfSt29fZs2a1aRcQqPRSFZWFp06dUImk1FaWoqfnx86nQ69Xo+rqys6nY7S0tI6tTRryc3NxdvbG3d3d0pKSujQoQNSqZTs7GyraMdaOnXqhFqtplevXphMJu666y5LVGJWVhaBgYE4OztbZjg6nY6UlBT8/f0tM57rI9s9PDwYOnSoTe87KysLZ2dnK8kxpVKJUqm03GdPnz5tFd0J5oefYcOGodfrKSwspGPHjha5Na1WS0ZGBmFhYU2SrKutGxgcHIyDg+2S1Onp6cjlcqul6PLycrRareV9HT9+HKXSOrXM29ubQYMGodPpKCoqIjg42PKZ+fbbb8nOzrZ6kKmrXS1Go5H09HQ6dOjQ4MPDtdj0Dt3d3YmPj2fLli1cuXKFoKAgpk2b1uCHEMwbprXBNJWVlSxZsoSLFy+yevVqlixZwsqVK/Hy8uLTTz9FJpPx6aefMmPGDCQSCUuXLqV79+6EhYWxb98+evToQUBAAF9//XWj9v5TN5xJYVrCc+peNrkZin06keY7iPO5TlTuKWbO0PnoirUcCDxPTYn9nCCYPxQyp6s2KEP64YZwhE1FHRgFlaCVtKIyUTtHIpFw3333ER4eTkJCgiVHrmPHjgwcOJA+ffo0OaFeKpVa7YnV3lQdHR0tN3NHR8dG7z/XxijYskcokUh45JFHGDt2LAkJCVZR8deKVNcu9To6Ot5Sgvn11CWELZfLbVraA3BwcLghLsPJyalOQfHGkEgkNgtzX0tdxX5tdUZgvqbXvocPPviA9evXc+DAgQbbXYtUKrUsA9uKTTPC+Ph4y2bktXh5eTF48GAmTJjQ6EBarZZ33nnH5nDWW2HD03+lQJFE6LAQusrz6Jd6EKmx6flVRomU1E4DSTF25fJZJX4mPwZGTsZb4YuxSs+xiFzOZd9akd3mYmzXQVw+LUdXYyA4WEaP//7B3ia1O7IWriZP4YFPdD6JmXVHJrZ1WntGeLuh0WhITk4mKCiowb1NQetQXFyMm5tbk2oz3gw2zQiTkpIsob118cknn1jyRurDZDI1mHfYnMS4T0AaMplCdTaxxzZxofd99PMvo0fmERwMDYeX62VO5PuGUuzbj/P5bpTsy6ZXVE/uixiEQ4EE8kwY0ZPevarNOEGAKpMWTz8HSnMN5kK9Do6gb1l5t9uNSr077t4yFNq2XX5J0HK4uLjQp08fe5sh+B+t9TBikyMcOnQowcHBfPPNN8TExHDy5Enmz5/PN998w9dff83WrVsbdYTOzs44Ozs3i9GNoUePQwX405E5EcsodSki9uD3HO82lf5hajqXJVLp7ofW1Y8amRdVRjcUNQ6UVZkoL9dgiK/Ex8WJgRH30KGnPyalHtQAJtSeRlI7lhOfZ7tqQWtQXFNBgEdHSgFdjYGaXiNxTtxvb7PaDxIpFRVGOnWVkV8tUicEgjsJmxzhTz/9BMDYsWMBGD58OE5OThw7dozRo0fzzjstH6XZFNa7HmFIUG+icjrgqNTho/Rhepc/UiEv42jcJg469sdUWgUmAx4eEBgQhJ9XCKGu/rj5euLs5QLFBig0YUKPSQoloTouO+aTnJuKMavtlToqqiwh0vOquEFVt8HCETYBfVhPdDVG3J0lVJZUNv4CwTWYyM/fQm7udyirzPJeco+7CAlZQFDQbJpcmbcFEaLbjVOX6PbNkpKSQqdOndp8AXebJNaioqLIy8tjypQprFixgpkzZ5KamkpkZCRr1qxpsEKxPTCajBzLO8MGl99I6JaPxt2ISa3HK9+TyR0XMyfqaeYPfpX50X9iqv8TDDKNo2tFFD75HXDOdYBCPRhNaDxNXO5RwQ9+8fxYcJhL2Sl1aqe2BarV1Tg4XF0KrXDpZEdr2h/qcHOIv9RJ12b/x20Rk8nIufPPc+HiS1QqTmM0ajAaNVQqTnPh4kucO/88pmaokSlEt+0rut0Ujh07xldffQXARx99RH5+frPY9fHHH9erKnSr2OQIZ82axZ///GcOHTrEX/7yF3bt2sWyZcuYOXMmTk5OrRIAczPUaGs4nXeBjbI4TkcWovYyYtIakOUZMRXrMamtc8V0LiYqAvVkh1VzsFsa/9Uf5EhGAhWK9jFD0DlUI5Wan76LFQ0rKQisKfAfDIBB1j6l1exFfv4mCgu313u+sHA7+fmb6jwnRLfbj+i2Xq+36vfy5csWFZqTJ0+ybds2CgoKMBqNHD58mF9++YWSkhKeffZZgoKCAHN6yKZNm6z+H+fPn6esrIydO3c26HzLysrYvXs3cXFx1NTUWL2flJSUOjWtm4JNjhDgrbfeorKykuzsbKqqqvjggw+QSCQcOXLEIunTVtFqtSRknWOD/jDHInIoCK0ho7uKpMgSYsMz2dHpPN96/8Y69rO58hB78o9yJS+93c0MqiQa5L7m8PLqKj267k2TfLpT0XeOIqdAgkQiQSsVjrAp5OZtvOk2QnS7/Yhul5WVWWm1Ll68mLy8PD777DNWrFhBZmYmEydOJCsri7Nnz5KVlUVubi5//OMfSUtL47fffmPOnDnk5OTw/PPP8+mnnwIwadIkHn/8cRISEhg1alS9s+WCggLy8/NJSEigrKzMco0AnnrqKUtVipvF9kxJzHkqtRpz7RGDwcC57Muc48Zk2tuBMp0CuZc/lf/TOq+OisHrSqJ9jWoHFI94CFOBCXdvR6qM7a/qhD1RqZJvqY0Q3W4fotuTJ0+uc9zTp0/To0cPFi1axKRJk/Dw8GDWrFnExcVZSbO9++67rFmzhqFDh/Lwww/Tr18/lixZgkql4t///jfe3t5kZGSQmJjIpEmTbhgnOjqanj17smDBghbZb7R5Riho+xRVXa1NCFDs3QMcWydSt71icnEjo8qcbO3h6UBljUimb36aLrp9zz338Ne//vWWRLfvv/9+nnnmGVJSUmyyMjs7m6ioKOBG0e0ZM2bw0ksvkZOTg8lkshLdHjJkCAkJCTaNUZet14puz5s3r1lEtydPnkxmZmaLiW7X9vXOO+/g7OzMPffcw1NPPUVVVd3fn2tt6dChg2Wca6vKe3h4WNWmtZVaW24F4QhvI8ory3F3uLqcm5Ur4djEjymc9zpG//Y7k29JlOMeRl1lFluQu8kor2qfYtv2wt29cdUSjwba1Ce6HRsbyxdffGGVSH0zotvffvutzeovDYlu79ixg6+++sqitnKt6PaRI0d4//33bRqjLmpFtzdu3MjGjRsJDQ21Et2Gxus+1opug7lk3ieffGIR3QZuSnQbsIhuu7m5WWTRFAqFZV/2o48+4plnnuHUqVOMGzfOIn95/cPLtbZcvnyZLl262GzL9bi4uKBSmXN9q6qqrAq5V1RUWMZWqVSWhyudTlevk4YmLo0K2j56BxUgs/xdXaXnfJU/Dv1epWuAmqDTm3C8cLT+DgBd9DAqe4ymxLkLBm010T++jMSG6tLtkUx5P6g2vzdXZ1BUKBt5heBaQkLmo1A0vPweHHK/zf0J0e22Kbrt4eFBr169GD9+PHBVDi48PJzp06fTp08f4uPj2bhxIxqNhmeffdYqQveNN97gwQcftNjy0UcfNfk69erVi+eff55Dhw4xZMgQxo4di0QisdquCwoKori4GA8PD5YsWcKYMWP4/e9/z65du/j8888tQt7XY5PEWnujrUaxtgYjuwwg+5IPqsr6VWUCA2WElp3A48B6JHo9JrkP1QMnUxYykPwqOVXXvTYyuIpO/72l4lZtkpo+I4nrcLWCSu9BjuzP2WdHi26d1hfdNnLh4nIKCuoWwu/Y8T6i71qFRGL74pMQ3W67otuFhYX4+PhY1fcrKyujoKCA8PBwi2hKdXU1Tk5OVq+ttaVr16711gc0Go3s339j/nOXLl2IiIhAoVDg6ekJmKN2vb29G601aAtiRnibUWlSI/fxRdVAxkdhoYFCBuI1YyhOjiZKig2YjCbIBbjRgSbneeA2cxkdfqw7Mq69UtB79v/esxmjw63vNdxpSCRSekb/Dd8OMeTmbUCpNC8tyuXRhATPp2PHWTQ1oV6Ibl+lrYluX+uka+nQoQMdOnSwOubm5nZDu5u15VpqnSCY9z2bCzEjvM3o6BdId1M/Lp9v3pu6RCphiPEI7ge/a9Z+7YXJJ5Ajg99ArzXnkkplEroOruR4RvuOshWi27eGEN2+MxHBMrcZJRWlyG1fAbEZk9HEKedRaHuNaP7O7UDpuMcsThAwp04YxIzwTqdWdFs4wTsL4QhvM/R6PTi2TC6crsZIYveHMQR2aZH+WwuTTEa6oavVMbmnDIVWpE4IBHciwhHehtRIVTi5yBpveBNUVeg4P/pP4GbbvkVbRD1yHsoK671QH3cdZUqROiEQ3IkIR3gbUmnS4OnbcnFQJUV6rtz3LjQhErAtkRM80upviVSCp1SNqlrUIRQI7kTa551M0CAl2ko85S1b+iYrV0LBvNdbdIyWQB/eh9zrxPB9gx2QyVpgY1UgELQLhCO8DSmqKMGrhZZGr+VCkS+Vk59s8XGak6IhC25Qvegg16CUae1kkUAgsDfCEd6GqDVqHKWtcGM3wVljPwwhbaseZX0Y3eRkVFrnO0mkEoIdZKQZmqdmmkAgaH+0qCN8//33LeKq17Nx40aefPJJ1qxZg8FgDmMvLS3l1VdfZenSpVYitnv37mXJkiW88847t1x36k5B66BEKmv5yuC6GiMZo59p8XGaA8W4h9FUW0vF+YU44FbjTGZRjp2sEggE9qZFHOHZs2d55ZVX+NOf/mQO57+O7du3s2bNGh555BESEhIsgrXz5s3D39+f2bNnc//991NUVMSpU6d4/vnnWbRoEZWVlVZqD4L6UUpqLLUJW5rMPBmqUbbrSdqLTNfeNxzz8dCQK1dYHsYEAsGdR4uEFqrVarp162Yp9XE969at49VXX2XYsGEEBwczbdo0Fi1aRG5uLs899xxgrtW1fft2Lly4wNNPP82IESMYOHAgoaGhfPLJJzelWn4nUapX4ukZSGVR64x30Xc8A113IFG3zVw8zaB7KS22fiiTSiWEODoQbxSzQYHgTqZFZoR33303ixcvrlNvDuDKlSt0727eV+rcubOl5EntMTDX38rKyrI67uLigpubGxUVIt+rMYqUpXi7td4WsKJcR/G0F1ptvKaSGzX9hmO+IQ641DiJZVGB4A7HLqLb1xaANBgMODo6Wh0Dc/2o+o5fqzYeGxtLXFxc6xnfTqhUVCI15SP380JZ0jpjXiwPRB7aA9esS403bkWKRz5AZu6NDwUuDuWkOhpuq2VRlUpFWlqavc0QCNoVdnGEERERJCcnEx0dTUpKCj169CA8PJwrV65gMpmQSCSkpKQwceJElEolycnJTJ48mYqKClxdXa2KdcbExBATE2PV/50sun0t7l5yyNxGx26zKGiFe6NBbyJrxDNEZT3V8oPZiCE0khT5aEvNwVqkUgnd3eWcdEy3k2Utg7u7e6OC2sJRCgTWtJojLCkp4YknnmDr1q08/vjjvPjii+j1ej7//HOWLFlCcHAwPXv25OWXXyYqKorffvuNv//97/To0YMZM2YQGBjIjz/+yOOPP95aJrd7KiQ1TAhYwInyXwjs2oOizIAbcuiam9x8EyHjFuGx/5sWHccWTDIZl4cvQ1NwY8CWb4gMV52MzDKxLCo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aria-label=\"hour: 0; gen_sum: 42; resource: hydroelectric_pumped_storage\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,118.451L8.333,122.364L16.667,121.24L25,117.894L33.333,106.981L41.667,96.444L50,86.761L58.333,100.046L66.667,144.317L75,151.32L83.333,149.967L91.667,160.134L100,173.655L108.333,173.655L116.667,173.655L125,173.655L133.333,159.833L141.667,134.96L150,78.066L158.333,62.001L166.667,62.314L175,77.865L183.333,95.032L191.667,109.086L191.667,111.486L183.333,97.432L175,80.265L166.667,64.714L158.333,64.401L150,80.466L141.667,137.36L133.333,162.233L125,173.655L116.667,173.655L108.333,173.655L100,173.655L91.667,162.534L83.333,152.367L75,153.72L66.667,146.717L58.333,102.446L50,89.161L41.667,98.844L33.333,109.381L25,120.294L16.667,123.64L8.333,124.764L0,120.851Z\" fill=\"#e377c2\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 1385.106268; resource: natural_gas_fired_combined_cycle\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,120.851L8.333,124.764L16.667,123.64L25,120.294L33.333,109.381L41.667,98.844L50,89.161L58.333,102.446L66.667,146.717L75,153.72L83.333,152.367L91.667,162.534L100,173.655L108.333,173.655L116.667,173.655L125,173.655L133.333,162.233L141.667,137.36L150,80.466L158.333,64.401L166.667,64.714L175,80.265L183.333,97.432L191.667,111.486L191.667,200L183.333,188.432L175,171.265L166.667,155.714L158.333,155.401L150,171.466L141.667,200L133.333,200L125,200L116.667,200L108.333,200L100,200L91.667,200L83.333,200L75,200L66.667,200L58.333,198.092L50,198.092L41.667,200L33.333,200L25,200L16.667,200L8.333,200L0,200Z\" fill=\"#7f7f7f\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 0; resource: natural_gas_fired_combustion_turbine\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,200L8.333,200L16.667,200L25,200L33.333,200L41.667,200L50,198.092L58.333,198.092L66.667,200L75,200L83.333,200L91.667,200L100,200L108.333,200L116.667,200L125,200L133.333,200L141.667,200L150,171.466L158.333,155.401L166.667,155.714L175,171.265L183.333,188.432L191.667,200L191.667,200L183.333,200L175,200L166.667,200L158.333,200L150,200L141.667,200L133.333,200L125,200L116.667,200L108.333,200L100,200L91.667,200L83.333,200L75,200L66.667,200L58.333,200L50,200L41.667,200L33.333,200L25,200L16.667,200L8.333,200L0,200Z\" fill=\"#bcbd22\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 163.3088; resource: _onshore_wind_turbine\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" 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role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 0; resource: _solar_photovoltaic\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,117.228L8.333,121.142L16.667,120.017L25,116.671L33.333,105.758L41.667,95.221L50,72.582L58.333,47.023L66.667,31.199L75,15.219L83.333,7.259L91.667,15.083L100,22.634L108.333,25.526L116.667,31.288L125,40.229L133.333,49.011L141.667,57.923L150,65.667L158.333,60.778L166.667,61.092L175,76.642L183.333,93.809L191.667,107.863L191.667,107.863L183.333,93.809L175,76.642L166.667,61.092L158.333,60.778L150,75.207L141.667,122.643L133.333,142.571L125,154.129L116.667,152.257L108.333,151.523L100,151.554L91.667,137.863L83.333,128.039L75,130.359L66.667,126.719L58.333,91.243L50,83.642L41.667,95.221L33.333,105.758L25,116.671L16.667,120.017L8.333,121.142L0,117.228Z\" fill=\"#d62728\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 0; resource: _solar_photovoltaic_btm\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,117.228L8.333,121.142L16.667,120.017L25,116.671L33.333,105.758L41.667,95.221L50,83.642L58.333,91.243L66.667,126.719L75,130.359L83.333,128.039L91.667,137.863L100,151.554L108.333,151.523L116.667,152.257L125,154.129L133.333,142.571L141.667,122.643L150,75.207L158.333,60.778L166.667,61.092L175,76.642L183.333,93.809L191.667,107.863L191.667,107.863L183.333,93.809L175,76.642L166.667,61.092L158.333,60.778L150,76.843L141.667,133.737L133.333,158.61L125,173.655L116.667,173.655L108.333,173.655L100,173.655L91.667,158.911L83.333,148.744L75,150.097L66.667,143.094L58.333,98.823L50,85.538L41.667,95.221L33.333,105.758L25,116.671L16.667,120.017L8.333,121.142L0,117.228Z\" fill=\"#9467bd\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 0; resource: _curtailment\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,107.714L8.333,111.257L16.667,113.257L25,110.743L33.333,100.971L41.667,87.086L50,68.161L58.333,44.019L66.667,21.454L75,7.519L83.333,0.723L91.667,9.638L100,19.476L108.333,18.545L116.667,24.442L125,36.309L133.333,45.561L141.667,53.248L150,62.479L158.333,57.086L166.667,56.8L175,70.971L183.333,86.4L191.667,99.429L191.667,99.429L183.333,86.4L175,70.971L166.667,56.8L158.333,57.086L150,62.479L141.667,53.248L133.333,45.561L125,38.646L116.667,31.288L108.333,25.526L100,21.157L91.667,9.638L83.333,0.723L75,7.519L66.667,21.454L58.333,44.019L50,68.161L41.667,87.086L33.333,100.971L25,110.743L16.667,113.257L8.333,111.257L0,107.714Z\" fill=\"#1f77b4\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g></g><g class=\"mark-group role-legend\" role=\"graphics-symbol\" aria-roledescription=\"legend\" aria-label=\"Symbol legend titled 'resource' for fill color with 9 values: _curtailment, _onshore_wind_turbine, _small_hydroelectric, _solar_photovoltaic, _solar_photovoltaic_btm, ending with natural_gas_fired_combustion_turbine\"><g transform=\"translate(218,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h174v131h-174Z\" pointer-events=\"none\"/><g><g class=\"mark-group role-legend-entry\"><g transform=\"translate(0,16)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"/><g><g class=\"mark-group role-scope\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#1f77b4\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_curtailment</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,13)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#ff7f0e\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_onshore_wind_turbine</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,26)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#2ca02c\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_small_hydroelectric</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,39)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#d62728\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_solar_photovoltaic</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,52)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#9467bd\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_solar_photovoltaic_btm</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,65)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#8c564b\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">biomass</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,78)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#e377c2\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">hydroelectric_pumped_storage</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,91)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#7f7f7f\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">natural_gas_fired_combined_cycle</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,104)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#bcbd22\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">natural_gas_fired_combustion_tu…</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g><g class=\"mark-text role-legend-title\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(0,9)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">resource</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g></g></g></svg>"
      ],
      "text/plain": [
       "@vlplot(\n",
       "    mark=\"area\",\n",
       "    encoding={\n",
       "        x={\n",
       "            field=\"hour\"\n",
       "        },\n",
       "        y={\n",
       "            stack=\"zero\",\n",
       "            field=\"gen_sum\"\n",
       "        },\n",
       "        color={\n",
       "            scale={\n",
       "                scheme=\"category10\"\n",
       "            },\n",
       "            field=\"resource\",\n",
       "            type=\"nominal\"\n",
       "        }\n",
       "    },\n",
       "    data={\n",
       "        values=...\n",
       "    }\n",
       ")"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Add in BTM solar and curtailment and plot results\n",
    "\n",
    "sol_gen = innerjoin(solution.gen, \n",
    "                    gen_df[!, [:r_id, :resource]], \n",
    "                    on = :r_id)\n",
    "sol_gen = combine(groupby(sol_gen, [:resource, :hour]), \n",
    "            :gen => sum)\n",
    "\n",
    "# Rename generators (for plotting purposes)\n",
    "sol_gen[sol_gen.resource .== \"solar_photovoltaic\", :resource] .= \"_solar_photovoltaic\"\n",
    "sol_gen[sol_gen.resource .== \"onshore_wind_turbine\", :resource] .= \"_onshore_wind_turbine\"\n",
    "sol_gen[sol_gen.resource .== \"small_hydroelectric\", :resource] .= \"_small_hydroelectric\"\n",
    "\n",
    "# BTM solar\n",
    "btm = DataFrame(resource = repeat([\"_solar_photovoltaic_btm\"]; outer=length(T_period)), \n",
    "    hour = T_period,\n",
    "    gen_sum = gen_variable_multi[gen_variable_multi.gen_full .== \"wec_sdge_solar_photovoltaic_1.0\",:cf] * 600)\n",
    "append!(sol_gen, btm)\n",
    "\n",
    "# Curtailment\n",
    "curtail = combine(groupby(solution.curtail, [:hour]),\n",
    "            :curt => sum)\n",
    "curtail[!, :resource] .= \"_curtailment\"\n",
    "rename!(curtail, :curt_sum => :gen_sum)\n",
    "append!(sol_gen, curtail[:,[:resource, :hour, :gen_sum]])\n",
    "\n",
    "# Rescale hours\n",
    "sol_gen.hour = sol_gen.hour .- T_period[1]\n",
    "\n",
    "sol_gen |>\n",
    "@vlplot(:area, \n",
    "    x=:hour, y={:gen_sum, stack=:zero}, \n",
    "    color={\"resource:n\", scale={scheme=\"category10\"}})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that the combined cycle plants flatten out during the day, but don't shut down due to the need for ramping capabilities in the late afternoon/evening, when solar output falls off and evening demand remains strong. This leads to some curtailment of solar from 11:00 - 16:00, which was not present in the Economic Dispatch model. All curtailment is lumped together as the model does not accurately distinguish between whether wind, solar or hydro is curtailed, which in practice is up to the system operator and depends on a variety of factors such as location, interconnection voltage, etc."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can examine the commitment status of various units by examining the results in `solution.commit`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
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         "title": "hour",
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        {
         "grid": false,
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       ],
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          },
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           "gen_sum": 0,
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class=\"mark-group role-legend-entry\"><g transform=\"translate(0,16)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"/><g><g class=\"mark-group role-scope\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#1f77b4\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">natural_gas_fired_combined_cycle</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g 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font-weight=\"bold\" fill=\"#000\" opacity=\"1\">resource</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g></g></g></svg>"
      ],
      "text/plain": [
       "@vlplot(\n",
       "    mark=\"area\",\n",
       "    encoding={\n",
       "        x={\n",
       "            field=\"hour\"\n",
       "        },\n",
       "        y={\n",
       "            stack=\"zero\",\n",
       "            field=\"gen_sum\"\n",
       "        },\n",
       "        color={\n",
       "            scale={\n",
       "                scheme=\"category10\"\n",
       "            },\n",
       "            field=\"resource\",\n",
       "            type=\"nominal\"\n",
       "        }\n",
       "    },\n",
       "    data={\n",
       "        values=...\n",
       "    }\n",
       ")"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sol_commit = innerjoin(solution.commit, \n",
    "                    gen_df[!, [:r_id, :resource]], \n",
    "                    on = :r_id)\n",
    "sol_commit = combine(groupby(sol_commit, [:resource, :hour]), \n",
    "            :gen => sum)\n",
    "sol_commit.hour = sol_commit.hour .- T_period[1]\n",
    "\n",
    "sol_commit |>\n",
    "@vlplot(:area, \n",
    "    x=:hour, y={:gen_sum, stack=:zero}, \n",
    "    color={\"resource:n\", scale={scheme=\"category10\"}})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that units shutdown during the solar period and startup for the evening peak. However, due to the commitment constraints, not all natural gas plants can be decommitted, resulting in the observed curtailment. A large number of combustion turbines turn on to meet the evening peak."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Moderate complexity unit commitment\n",
    "\n",
    "We expand the above unit commitment with ramp equations. These must be modified to prevent ramp violations during the startup process. In order to accommodate this, we introduce an **auxiliary variable** $GENAUX_{g,t}$ defined as the generation above the minimum output (if committed). $GENAUX_{g,t} = GEN_{g,t} = 0$ if the unit is not committed. Auxiliary variables are for convenience (we could always write the whole problem in terms of the original decision variables), but they help de-clutter the model and in general won't add too much computational penalty. The following constraints are added:\n",
    "\n",
    "$$\n",
    "\\begin{align}\n",
    " & GENAUX_{g,t} = GEN_{g,t} - Pmin_{g,t}COMMIT_{g,t} & \\forall \\quad g \\in G_{thermal} , t \\in T \\\\\n",
    " & GENAUX_{g,t+1} - GENAUX_{g,t} \\leq RampUp_{g} & \\forall \\quad g \\in G_{thermal} , t = 1..T-1 \\\\\n",
    "  & GENAUX_{g,t} - GENAUX_{g,t+1} \\leq RampDn_{g} & \\forall \\quad g \\in G_{thermal} , t = 1..T-1 \\\\\n",
    " & GEN_{g,t+1} - GEN_{g,t} \\leq RampUp_{g} & \\forall \\quad g \\notin G_{thermal} , t = 1..T-1 \\\\\n",
    "  & GEN_{g,t} - GEN_{g,t+1} \\leq RampDn_{g} & \\forall \\quad g \\notin G_{thermal} , t = 1..T-1  \n",
    "\\end{align}\n",
    "$$\n",
    "\n",
    "The creation of this auxiliary variable $GENAUX$ helps us avoid violating ramping constraints when we start up our units and their generation immediately jumps up to their minium output level or during shut-down when a unit drops from minimum output (or above) to zero. \n",
    "\n",
    "Note you may encounter alternative formulations in the literature to address this start-up and shut-down that modify the right-hand side of the traditional ramping constraint on total generation to account for the additional step change in output during start-up or shut-down periods. The above formulation is conceptually simple and works well."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Create solver function\n",
    "\n",
    "(We reuse steps 1 and 2 above to load packages and data.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "unit_commitment_ramp (generic function with 1 method)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#=\n",
    "Function to solve moderate complexity unit commitment problem (commitment and ramp equations)\n",
    "Inputs:\n",
    "    gen_df -- dataframe with generator info\n",
    "    loads  -- load by time\n",
    "    gen_variable -- capacity factors of variable generators (in \"long\" format)\n",
    "    mip_gap -- desired relative MIP gap to pass to solver\n",
    "=#\n",
    "function unit_commitment_ramp(gen_df, loads, gen_variable, mip_gap)\n",
    "    UC = Model(HiGHS.Optimizer)\n",
    "    set_optimizer_attribute(UC, \"mip_rel_gap\", mip_gap) \n",
    "\n",
    "    # Define sets based on data\n",
    "    # Note the creation of several different sets of generators for use in\n",
    "    # different equations.\n",
    "    G_thermal = gen_df[gen_df[!,:up_time] .> 0,:r_id]\n",
    "    G_nonthermal = gen_df[gen_df[!,:up_time] .== 0,:r_id]\n",
    "    G_var = gen_df[gen_df[!,:is_variable] .== 1,:r_id] \n",
    "    G_nonvar = gen_df[gen_df[!,:is_variable] .== 0,:r_id]\n",
    "    G_nt_nonvar = intersect(G_nonvar, G_nonthermal)\n",
    "    G = gen_df.r_id\n",
    "    T = loads.hour\n",
    "    T_red = loads.hour[1:end-1]  # reduced time periods without last one\n",
    "\n",
    "    # Generator capacity factor time series for variable generators\n",
    "    gen_var_cf = innerjoin(gen_variable, \n",
    "                    gen_df[gen_df.is_variable .== 1 , \n",
    "                        [:r_id, :gen_full, :existing_cap_mw]], \n",
    "                    on = :gen_full)\n",
    "        \n",
    "    # Decision variables   \n",
    "    @variables(UC, begin\n",
    "        GEN[G, T]  >= 0     # generation\n",
    "        GENAUX[G_thermal, T] >= 0 # auxiliary generation variable\n",
    "        COMMIT[G_thermal, T], Bin # commitment status (Bin=binary)\n",
    "        START[G_thermal, T], Bin  # startup decision\n",
    "        SHUT[G_thermal, T], Bin   # shutdown decision\n",
    "    end)\n",
    "                \n",
    "    # Objective function\n",
    "    @objective(UC, Min, \n",
    "        sum( (gen_df[gen_df.r_id .== i,:heat_rate_mmbtu_per_mwh][1] * gen_df[gen_df.r_id .== i,:fuel_cost][1] +\n",
    "            gen_df[gen_df.r_id .== i,:var_om_cost_per_mwh][1]) * GEN[i,t] \n",
    "                        for i in G_nonvar for t in T) + \n",
    "        sum(gen_df[gen_df.r_id .== i,:var_om_cost_per_mwh][1] * GEN[i,t] \n",
    "                        for i in G_var for t in T) + \n",
    "        sum(gen_df[gen_df.r_id .== i,:start_cost_per_mw][1] * \n",
    "            gen_df[gen_df.r_id .== i,:existing_cap_mw][1] *\n",
    "            START[i,t] \n",
    "                        for i in G_thermal for t in T)\n",
    "    )\n",
    "    \n",
    "    # Demand constraint\n",
    "    @constraint(UC, cDemand[t in T], \n",
    "        sum(GEN[i,t] for i in G) == loads[loads.hour .== t,:demand][1])\n",
    "\n",
    "    # Capacity constraints (thermal generators requiring commitment)\n",
    "    @constraint(UC, Cap_thermal_min[i in G_thermal, t in T], \n",
    "        GEN[i,t] >= COMMIT[i, t] * gen_df[gen_df.r_id .== i,:existing_cap_mw][1] *\n",
    "                        gen_df[gen_df.r_id .== i,:min_power][1])\n",
    "    @constraint(UC, Cap_thermal_max[i in G_thermal, t in T], \n",
    "        GEN[i,t] <= COMMIT[i, t] * gen_df[gen_df.r_id .== i,:existing_cap_mw][1])\n",
    "\n",
    "    # Capacity constraints (non-variable generation not requiring commitment)\n",
    "    @constraint(UC, Cap_nt_nonvar[i in G_nt_nonvar, t in T], \n",
    "        GEN[i,t] <= gen_df[gen_df.r_id .== i,:existing_cap_mw][1])\n",
    "\n",
    "    # Capacity constraints (variable generation)\n",
    "    @constraint(UC, Cap_var[i in 1:nrow(gen_var_cf)], \n",
    "            GEN[gen_var_cf[i,:r_id], gen_var_cf[i,:hour] ] <= \n",
    "                        gen_var_cf[i,:cf] *\n",
    "                        gen_var_cf[i,:existing_cap_mw])\n",
    "    \n",
    "    # Unit commitment constraints\n",
    "    @constraint(UC, Startup[i in G_thermal, t in T],\n",
    "        COMMIT[i, t] >= sum(START[i, tt] \n",
    "                        for tt in intersect(T,\n",
    "                            (t-gen_df[gen_df.r_id .== i,:up_time][1]):t)))\n",
    "\n",
    "    @constraint(UC, Shutdown[i in G_thermal, t in T],\n",
    "        1-COMMIT[i, t] >= sum(SHUT[i, tt] \n",
    "                        for tt in intersect(T,\n",
    "                            (t-gen_df[gen_df.r_id .== i,:down_time][1]):t)))\n",
    "    \n",
    "    @constraint(UC, CommitmentStatus[i in G_thermal, t in T_red],\n",
    "        COMMIT[i,t+1] - COMMIT[i,t] == START[i,t+1] - SHUT[i,t+1])\n",
    "    \n",
    "    # New auxiliary variable GENAUX for generation above the minimum output level\n",
    "    # for committed thermal units (only created for thermal generators)\n",
    "    @constraint(UC, AuxGen[i in G_thermal, t in T],\n",
    "        GENAUX[i,t] == GEN[i,t] - COMMIT[i, t] * gen_df[gen_df.r_id .== i,:existing_cap_mw][1] *\n",
    "                        gen_df[gen_df.r_id .== i,:min_power][1])\n",
    "    \n",
    "    # Ramp equations for thermal generators (constraining GENAUX)\n",
    "    @constraint(UC, RampUp_thermal[i in G_thermal, t in T_red], \n",
    "        GENAUX[i,t+1] - GENAUX[i,t] <= gen_df[gen_df.r_id .== i,:existing_cap_mw][1] * \n",
    "                                 gen_df[gen_df.r_id .== i,:ramp_up_percentage][1] )\n",
    "\n",
    "    @constraint(UC, RampDn_thermal[i in G_thermal, t in T_red], \n",
    "        GENAUX[i,t] - GENAUX[i,t+1] <= gen_df[gen_df.r_id .== i,:existing_cap_mw][1] * \n",
    "                                 gen_df[gen_df.r_id .== i,:ramp_dn_percentage][1] )\n",
    "\n",
    "    # Ramp equations for non-thermal generators (constraining total generation GEN)\n",
    "    @constraint(UC, RampUp_nonthermal[i in G_nonthermal, t in T_red], \n",
    "        GEN[i,t+1] - GEN[i,t] <= gen_df[gen_df.r_id .== i,:existing_cap_mw][1] * \n",
    "                                 gen_df[gen_df.r_id .== i,:ramp_up_percentage][1] )\n",
    "\n",
    "    @constraint(UC, RampDn[i in G, t in T_red], \n",
    "        GEN[i,t] - GEN[i,t+1] <= gen_df[gen_df.r_id .== i,:existing_cap_mw][1] * \n",
    "                                 gen_df[gen_df.r_id .== i,:ramp_dn_percentage][1] )\n",
    "      \n",
    "    \n",
    "    # Solve statement (! indicates runs in place)\n",
    "    optimize!(UC)\n",
    "\n",
    "    # Generation solution\n",
    "    gen = value_to_df_2dim(value.(GEN))\n",
    "\n",
    "    # Commitment status solution\n",
    "    commit = value_to_df_2dim(value.(COMMIT))\n",
    "\n",
    "    # Calculate curtailment\n",
    "    curtail = innerjoin(gen_var_cf, gen, on = [:r_id, :hour])\n",
    "    curtail.curt = curtail.cf .* curtail.existing_cap_mw - curtail.gen\n",
    "    \n",
    "    # Return the solution and objective as named tuple\n",
    "    return (\n",
    "        gen,\n",
    "        commit,\n",
    "        curtail,\n",
    "        cost = objective_value(UC),\n",
    "        status = termination_status(UC)\n",
    "    )\n",
    "\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. Solve a day's unit commitment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running HiGHS 1.5.3 [date: 1970-01-01, git hash: 45a127b78]\n",
      "Copyright (c) 2023 HiGHS under MIT licence terms\n",
      "Presolving model\n",
      "4230 rows, 2705 cols, 12697 nonzeros\n",
      "2978 rows, 1981 cols, 11613 nonzeros\n",
      "2058 rows, 1889 cols, 10517 nonzeros\n",
      "1942 rows, 1792 cols, 9838 nonzeros\n",
      "\n",
      "Solving MIP model with:\n",
      "   1942 rows\n",
      "   1792 cols (1216 binary, 0 integer, 0 implied int., 576 continuous)\n",
      "   9838 nonzeros\n",
      "\n",
      "        Nodes      |    B&B Tree     |            Objective Bounds              |  Dynamic Constraints |       Work      \n",
      "     Proc. InQueue |  Leaves   Expl. | BestBound       BestSol              Gap |   Cuts   InLp Confl. | LpIters     Time\n",
      "\n",
      "         0       0         0   0.00%   -18497.611619   inf                  inf        0      0      0         0     0.0s\n",
      "         0       0         0   0.00%   853909.258012   inf                  inf        0      0      6       484     0.0s\n",
      " C       0       0         0   0.00%   854200.982678   926742.140347      7.83%      771     29    102       558     0.1s\n",
      " L       0       0         0   0.00%   855649.603077   856762.830062      0.13%     4913     97    102      1534     1.6s\n",
      "\n",
      "Solving report\n",
      "  Status            Optimal\n",
      "  Primal bound      856762.830062\n",
      "  Dual bound        855691.230208\n",
      "  Gap               0.125% (tolerance: 1%)\n",
      "  Solution status   feasible\n",
      "                    856762.830062 (objective)\n",
      "                    0 (bound viol.)\n",
      "                    3.67462731415e-15 (int. viol.)\n",
      "                    0 (row viol.)\n",
      "  Timing            1.56 (total)\n",
      "                    0.02 (presolve)\n",
      "                    0.00 (postsolve)\n",
      "  Nodes             1\n",
      "  LP iterations     2536 (total)\n",
      "                    0 (strong br.)\n",
      "                    1050 (separation)\n",
      "                    991 (heuristics)\n"
     ]
    },
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          {
           "gen_sum": 21.4,
           "hour": 0,
           "resource": "biomass"
          },
          {
           "gen_sum": 42,
           "hour": 0,
           "resource": "hydroelectric_pumped_storage"
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           "gen_sum": 28.62,
           "hour": 18,
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           "hour": 20,
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           "hour": 21,
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           "hour": 22,
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           "hour": 23,
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           "gen_sum": 0,
           "hour": 0,
           "resource": "_curtailment"
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           "gen_sum": 0,
           "hour": 1,
           "resource": "_curtailment"
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           "gen_sum": 0,
           "hour": 2,
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           "hour": 3,
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           "hour": 6,
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           "hour": 7,
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           "hour": 8,
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           "hour": 9,
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           "gen_sum": 0,
           "hour": 10,
           "resource": "_curtailment"
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           "gen_sum": 0,
           "hour": 11,
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           "gen_sum": 29.418571999999823,
           "hour": 12,
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           "hour": 15,
           "resource": "_curtailment"
          },
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           "gen_sum": 0,
           "hour": 16,
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           "hour": 17,
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           "hour": 18,
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           "hour": 23,
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         ]
        },
        {
         "name": "data_0",
         "source": "source_0",
         "transform": [
          {
           "as": "hour",
           "expr": "toNumber(datum[\"hour\"])",
           "type": "formula"
          },
          {
           "field": "gen_sum",
           "groupby": [
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           ],
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            "gen_sum_end"
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           "field": "gen_sum",
           "groupby": [
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           ],
           "offset": "zero",
           "sort": {
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            "order": [
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           "type": "stack"
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       "height": 200,
       "legends": [
        {
         "fill": "color",
         "symbolType": "circle",
         "title": "resource"
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       ],
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         },
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           ],
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         },
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           "encode": {
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              "signal": "isValid(datum[\"hour\"]) && isFinite(+datum[\"hour\"]) && isValid(datum[\"gen_sum\"]) && isFinite(+datum[\"gen_sum\"])"
             },
             "description": {
              "signal": "\"hour: \" + (format(datum[\"hour\"], \"\")) + \"; gen_sum: \" + (format(datum[\"gen_sum\"], \"\")) + \"; resource: \" + (isValid(datum[\"resource\"]) ? datum[\"resource\"] : \"\"+datum[\"resource\"])"
             },
             "fill": {
              "field": "resource",
              "scale": "color"
             },
             "orient": {
              "value": "vertical"
             },
             "x": {
              "field": "hour",
              "scale": "x"
             },
             "y": {
              "field": "gen_sum_end",
              "scale": "y"
             },
             "y2": {
              "field": "gen_sum_start",
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             }
            }
           },
           "from": {
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           "sort": {
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           },
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           ],
           "type": "area"
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       "scales": [
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          "field": "hour"
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         "nice": true,
         "range": [
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           "signal": "width"
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         "type": "linear",
         "zero": false
        },
        {
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         },
         "name": "color",
         "range": {
          "scheme": "category10"
         },
         "type": "ordinal"
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       "style": "cell",
       "width": 200
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aria-label=\"hour: 0; gen_sum: 42; resource: hydroelectric_pumped_storage\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,103.645L8.333,107.069L16.667,106.085L25,103.157L33.333,93.608L41.667,84.388L50,75.916L58.333,87.54L66.667,126.277L75,132.405L83.333,131.221L91.667,140.117L100,151.948L108.333,151.948L116.667,151.948L125,151.948L133.333,139.854L141.667,118.09L150,68.308L158.333,54.251L166.667,54.525L175,68.132L183.333,83.153L191.667,95.45L191.667,97.55L183.333,85.253L175,70.232L166.667,56.625L158.333,56.351L150,70.408L141.667,120.19L133.333,141.954L125,151.948L116.667,151.948L108.333,151.948L100,151.948L91.667,142.217L83.333,133.321L75,134.505L66.667,128.377L58.333,89.64L50,78.016L41.667,86.488L33.333,95.708L25,105.257L16.667,108.185L8.333,109.169L0,105.745Z\" fill=\"#e377c2\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 1364.124568; resource: natural_gas_fired_combined_cycle\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,105.745L8.333,109.169L16.667,108.185L25,105.257L33.333,95.708L41.667,86.488L50,78.016L58.333,89.64L66.667,128.377L75,134.505L83.333,133.321L91.667,142.217L100,151.948L108.333,151.948L116.667,151.948L125,151.948L133.333,141.954L141.667,120.19L150,70.408L158.333,56.351L166.667,56.625L175,70.232L183.333,85.253L191.667,97.55L191.667,160.375L183.333,148.078L175,133.057L166.667,119.45L158.333,119.176L150,133.233L141.667,175L133.333,175L125,175L116.667,175L108.333,175L100,175L91.667,175L83.333,175L75,175L66.667,175L58.333,175L50,173.951L41.667,173.951L33.333,173.951L25,173.951L16.667,173.951L8.333,173.951L0,173.951Z\" fill=\"#7f7f7f\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 20.9817; resource: natural_gas_fired_combustion_turbine\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,173.951L8.333,173.951L16.667,173.951L25,173.951L33.333,173.951L41.667,173.951L50,173.951L58.333,175L66.667,175L75,175L83.333,175L91.667,175L100,175L108.333,175L116.667,175L125,175L133.333,175L141.667,175L150,133.233L158.333,119.176L166.667,119.45L175,133.057L183.333,148.078L191.667,160.375L191.667,175L183.333,175L175,175L166.667,175L158.333,175L150,175L141.667,175L133.333,175L125,175L116.667,175L108.333,175L100,175L91.667,175L83.333,175L75,175L66.667,175L58.333,175L50,175L41.667,175L33.333,175L25,175L16.667,175L8.333,175L0,175Z\" fill=\"#bcbd22\"/></g></g><path class=\"foreground\" 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aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 0; resource: _solar_photovoltaic_btm\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,102.575L8.333,105.999L16.667,105.015L25,102.087L33.333,92.538L41.667,83.318L50,73.187L58.333,79.837L66.667,110.879L75,114.064L83.333,112.034L91.667,120.63L100,132.61L108.333,132.583L116.667,133.225L125,134.863L133.333,124.75L141.667,107.312L150,65.807L158.333,53.181L166.667,53.455L175,67.062L183.333,82.083L191.667,94.38L191.667,94.38L183.333,82.083L175,67.062L166.667,53.455L158.333,53.181L150,67.238L141.667,117.02L133.333,138.784L125,151.948L116.667,151.948L108.333,151.948L100,151.948L91.667,139.047L83.333,130.151L75,131.335L66.667,125.207L58.333,86.47L50,74.846L41.667,83.318L33.333,92.538L25,102.087L16.667,105.015L8.333,105.999L0,102.575Z\" fill=\"#9467bd\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 0; resource: _curtailment\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,94.25L8.333,97.35L16.667,99.1L25,96.9L33.333,88.35L41.667,76.2L50,59.641L58.333,38.517L66.667,18.772L75,6.579L83.333,0.633L91.667,8.433L100,17.041L108.333,16.227L116.667,21.387L125,31.771L133.333,39.866L141.667,46.592L150,54.669L158.333,49.95L166.667,49.7L175,62.1L183.333,75.6L191.667,87L191.667,87L183.333,75.6L175,62.1L166.667,49.7L158.333,49.95L150,54.669L141.667,46.592L133.333,39.866L125,33.815L116.667,27.377L108.333,22.335L100,18.512L91.667,8.433L83.333,0.633L75,6.579L66.667,18.772L58.333,38.517L50,59.641L41.667,76.2L33.333,88.35L25,96.9L16.667,99.1L8.333,97.35L0,94.25Z\" fill=\"#1f77b4\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g></g><g class=\"mark-group role-legend\" role=\"graphics-symbol\" aria-roledescription=\"legend\" aria-label=\"Symbol legend titled 'resource' for fill color with 9 values: _curtailment, _onshore_wind_turbine, _small_hydroelectric, _solar_photovoltaic, _solar_photovoltaic_btm, ending with natural_gas_fired_combustion_turbine\"><g transform=\"translate(218,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h174v131h-174Z\" pointer-events=\"none\"/><g><g class=\"mark-group role-legend-entry\"><g transform=\"translate(0,16)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"/><g><g class=\"mark-group role-scope\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#1f77b4\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_curtailment</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,13)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#ff7f0e\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_onshore_wind_turbine</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,26)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#2ca02c\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_small_hydroelectric</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,39)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#d62728\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_solar_photovoltaic</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,52)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#9467bd\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_solar_photovoltaic_btm</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,65)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#8c564b\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">biomass</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,78)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#e377c2\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">hydroelectric_pumped_storage</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,91)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#7f7f7f\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">natural_gas_fired_combined_cycle</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,104)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#bcbd22\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">natural_gas_fired_combustion_tu…</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g><g class=\"mark-text role-legend-title\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(0,9)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">resource</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g></g></g></svg>"
      ],
      "text/plain": [
       "@vlplot(\n",
       "    mark=\"area\",\n",
       "    encoding={\n",
       "        x={\n",
       "            field=\"hour\"\n",
       "        },\n",
       "        y={\n",
       "            stack=\"zero\",\n",
       "            field=\"gen_sum\"\n",
       "        },\n",
       "        color={\n",
       "            scale={\n",
       "                scheme=\"category10\"\n",
       "            },\n",
       "            field=\"resource\",\n",
       "            type=\"nominal\"\n",
       "        }\n",
       "    },\n",
       "    data={\n",
       "        values=...\n",
       "    }\n",
       ")"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solution = unit_commitment_ramp(\n",
    "    gen_df_sens, loads_multi, gen_variable_multi, 0.01); # 1% MIP gap\n",
    "\n",
    "# Add in BTM solar and curtailment and plot results\n",
    "\n",
    "sol_gen = innerjoin(solution.gen, \n",
    "                    gen_df[!, [:r_id, :resource]], \n",
    "                    on = :r_id)\n",
    "sol_gen = combine(groupby(sol_gen, [:resource, :hour]), \n",
    "            :gen => sum)\n",
    "\n",
    "# Rename generators (for plotting purposes)\n",
    "sol_gen[sol_gen.resource .== \"solar_photovoltaic\", :resource] .= \"_solar_photovoltaic\"\n",
    "sol_gen[sol_gen.resource .== \"onshore_wind_turbine\", :resource] .= \"_onshore_wind_turbine\"\n",
    "sol_gen[sol_gen.resource .== \"small_hydroelectric\", :resource] .= \"_small_hydroelectric\"\n",
    "\n",
    "# BTM solar\n",
    "btm = DataFrame(resource = repeat([\"_solar_photovoltaic_btm\"]; outer=length(T_period)), \n",
    "    hour = T_period,\n",
    "    gen_sum = gen_variable_multi[gen_variable_multi.gen_full .== \"wec_sdge_solar_photovoltaic_1.0\",:cf] * 600)\n",
    "append!(sol_gen, btm)\n",
    "\n",
    "# Curtailment\n",
    "curtail = combine(groupby(solution.curtail, [:hour]),\n",
    "            :curt => sum)\n",
    "curtail[!, :resource] .= \"_curtailment\"\n",
    "rename!(curtail, :curt_sum => :gen_sum)\n",
    "append!(sol_gen, curtail[:,[:resource, :hour, :gen_sum]])\n",
    "\n",
    "# Rescale hours\n",
    "sol_gen.hour = sol_gen.hour .- T_period[1]\n",
    "\n",
    "sol_gen |>\n",
    "@vlplot(:area, \n",
    "    x=:hour, y={:gen_sum, stack=:zero}, \n",
    "    color={\"resource:n\", scale={scheme=\"category10\"}})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In contrast to when we added ramp constraints to the Economic Dispatch problem, adding ramp constraints to our Unit Commitment formulation does not change the solution as much (at least in this case). Much of the inflexibility here arises from the unit commitment constraints, and once committed, there is ample ramping capability. We do however get relatively more combustion turbines running to meet the evening ramp, given their faster ramp rates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.vega.v5+json": {
       "$schema": "https://vega.github.io/schema/vega/v5.json",
       "axes": [
        {
         "aria": false,
         "domain": false,
         "grid": true,
         "gridScale": "y",
         "labels": false,
         "maxExtent": 0,
         "minExtent": 0,
         "orient": "bottom",
         "scale": "x",
         "tickCount": {
          "signal": "ceil(width/40)"
         },
         "ticks": false,
         "zindex": 0
        },
        {
         "aria": false,
         "domain": false,
         "grid": true,
         "gridScale": "x",
         "labels": false,
         "maxExtent": 0,
         "minExtent": 0,
         "orient": "left",
         "scale": "y",
         "tickCount": {
          "signal": "ceil(height/40)"
         },
         "ticks": false,
         "zindex": 0
        },
        {
         "grid": false,
         "labelFlush": true,
         "labelOverlap": true,
         "orient": "bottom",
         "scale": "x",
         "tickCount": {
          "signal": "ceil(width/40)"
         },
         "title": "hour",
         "zindex": 0
        },
        {
         "grid": false,
         "labelOverlap": true,
         "orient": "left",
         "scale": "y",
         "tickCount": {
          "signal": "ceil(height/40)"
         },
         "title": "gen_sum",
         "zindex": 0
        }
       ],
       "background": "white",
       "data": [
        {
         "name": "source_0",
         "values": [
          {
           "gen_sum": 6,
           "hour": 0,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 1,
           "hour": 0,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 6,
           "hour": 1,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 1,
           "hour": 1,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 6,
           "hour": 2,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 1,
           "hour": 2,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 6,
           "hour": 3,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 1,
           "hour": 3,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 6,
           "hour": 4,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 1,
           "hour": 4,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 6,
           "hour": 5,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 1,
           "hour": 5,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 6,
           "hour": 6,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 1,
           "hour": 6,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 5.999999999999998,
           "hour": 7,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 0,
           "hour": 7,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 8,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 0,
           "hour": 8,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 9,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 0,
           "hour": 9,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 10,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 0,
           "hour": 10,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 11,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 0,
           "hour": 11,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 12,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 0,
           "hour": 12,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 13,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 0,
           "hour": 13,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 14,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 0,
           "hour": 14,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 15,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 0,
           "hour": 15,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 16,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": -1.1102230246251565e-15,
           "hour": 16,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 17,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": -1.9984014443252818e-15,
           "hour": 17,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 18,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 10,
           "hour": 18,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 19,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 14.000000000000002,
           "hour": 19,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 20,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 13.999999999999995,
           "hour": 20,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 21,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 11,
           "hour": 21,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 22,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 6.999999999999997,
           "hour": 22,
           "resource": "natural_gas_fired_combustion_turbine"
          },
          {
           "gen_sum": 4,
           "hour": 23,
           "resource": "natural_gas_fired_combined_cycle"
          },
          {
           "gen_sum": 3.9999999999999982,
           "hour": 23,
           "resource": "natural_gas_fired_combustion_turbine"
          }
         ]
        },
        {
         "name": "data_0",
         "source": "source_0",
         "transform": [
          {
           "as": "hour",
           "expr": "toNumber(datum[\"hour\"])",
           "type": "formula"
          },
          {
           "field": "gen_sum",
           "groupby": [
            "resource"
           ],
           "key": "hour",
           "method": "value",
           "type": "impute",
           "value": 0
          },
          {
           "as": [
            "gen_sum_start",
            "gen_sum_end"
           ],
           "field": "gen_sum",
           "groupby": [
            "hour"
           ],
           "offset": "zero",
           "sort": {
            "field": [
             "resource"
            ],
            "order": [
             "descending"
            ]
           },
           "type": "stack"
          }
         ]
        }
       ],
       "height": 200,
       "legends": [
        {
         "fill": "color",
         "symbolType": "circle",
         "title": "resource"
        }
       ],
       "marks": [
        {
         "encode": {
          "update": {
           "height": {
            "field": {
             "group": "height"
            }
           },
           "width": {
            "field": {
             "group": "width"
            }
           }
          }
         },
         "from": {
          "facet": {
           "data": "data_0",
           "groupby": [
            "resource"
           ],
           "name": "faceted_path_main"
          }
         },
         "marks": [
          {
           "encode": {
            "update": {
             "defined": {
              "signal": "isValid(datum[\"hour\"]) && isFinite(+datum[\"hour\"]) && isValid(datum[\"gen_sum\"]) && isFinite(+datum[\"gen_sum\"])"
             },
             "description": {
              "signal": "\"hour: \" + (format(datum[\"hour\"], \"\")) + \"; gen_sum: \" + (format(datum[\"gen_sum\"], \"\")) + \"; resource: \" + (isValid(datum[\"resource\"]) ? datum[\"resource\"] : \"\"+datum[\"resource\"])"
             },
             "fill": {
              "field": "resource",
              "scale": "color"
             },
             "orient": {
              "value": "vertical"
             },
             "x": {
              "field": "hour",
              "scale": "x"
             },
             "y": {
              "field": "gen_sum_end",
              "scale": "y"
             },
             "y2": {
              "field": "gen_sum_start",
              "scale": "y"
             }
            }
           },
           "from": {
            "data": "faceted_path_main"
           },
           "name": "marks",
           "sort": {
            "field": "datum[\"hour\"]"
           },
           "style": [
            "area"
           ],
           "type": "area"
          }
         ],
         "name": "pathgroup",
         "type": "group"
        }
       ],
       "padding": 5,
       "scales": [
        {
         "domain": {
          "data": "data_0",
          "field": "hour"
         },
         "name": "x",
         "nice": true,
         "range": [
          0,
          {
           "signal": "width"
          }
         ],
         "type": "linear",
         "zero": false
        },
        {
         "domain": {
          "data": "data_0",
          "fields": [
           "gen_sum_start",
           "gen_sum_end"
          ]
         },
         "name": "y",
         "nice": true,
         "range": [
          {
           "signal": "height"
          },
          0
         ],
         "type": "linear",
         "zero": true
        },
        {
         "domain": {
          "data": "data_0",
          "field": "resource",
          "sort": true
         },
         "name": "color",
         "range": {
          "scheme": "category10"
         },
         "type": "ordinal"
        }
       ],
       "style": "cell",
       "width": 200
      },
      "image/png": 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pointer-events=\"none\"><line transform=\"translate(0,200)\" x2=\"0\" y2=\"-200\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"/></g><g class=\"mark-text role-axis-title\" pointer-events=\"none\"><text text-anchor=\"middle\" transform=\"translate(-22.123046875,100) rotate(-90) translate(0,-2)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">gen_sum</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g><g class=\"mark-group role-scope pathgroup\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 6; resource: natural_gas_fired_combined_cycle\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,110L8.333,110L16.667,110L25,110L33.333,110L41.667,110L50,110L58.333,120L66.667,140L75,140L83.333,140L91.667,140L100,140L108.333,140L116.667,140L125,140L133.333,140L141.667,140L150,40L158.333,0L166.667,0L175,30L183.333,70L191.667,100L191.667,140L183.333,110L175,70L166.667,40L158.333,40L150,80L141.667,180L133.333,180L125,180L116.667,180L108.333,180L100,180L91.667,180L83.333,180L75,180L66.667,180L58.333,180L50,170L41.667,170L33.333,170L25,170L16.667,170L8.333,170L0,170Z\" fill=\"#1f77b4\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 1; resource: natural_gas_fired_combustion_turbine\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,170L8.333,170L16.667,170L25,170L33.333,170L41.667,170L50,170L58.333,180L66.667,180L75,180L83.333,180L91.667,180L100,180L108.333,180L116.667,180L125,180L133.333,180L141.667,180L150,80L158.333,40L166.667,40L175,70L183.333,110L191.667,140L191.667,180L183.333,180L175,180L166.667,180L158.333,180L150,180L141.667,180L133.333,180L125,180L116.667,180L108.333,180L100,180L91.667,180L83.333,180L75,180L66.667,180L58.333,180L50,180L41.667,180L33.333,180L25,180L16.667,180L8.333,180L0,180Z\" fill=\"#ff7f0e\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g></g><g class=\"mark-group role-legend\" role=\"graphics-symbol\" aria-roledescription=\"legend\" aria-label=\"Symbol legend titled 'resource' for fill color with 2 values: natural_gas_fired_combined_cycle, natural_gas_fired_combustion_turbine\"><g transform=\"translate(218,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h174v40h-174Z\" pointer-events=\"none\"/><g><g class=\"mark-group role-legend-entry\"><g transform=\"translate(0,16)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"/><g><g class=\"mark-group role-scope\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#1f77b4\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">natural_gas_fired_combined_cycle</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,13)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#ff7f0e\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">natural_gas_fired_combustion_tu…</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g><g class=\"mark-text role-legend-title\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(0,9)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">resource</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g></g></g></svg>"
      ],
      "text/plain": [
       "@vlplot(\n",
       "    mark=\"area\",\n",
       "    encoding={\n",
       "        x={\n",
       "            field=\"hour\"\n",
       "        },\n",
       "        y={\n",
       "            stack=\"zero\",\n",
       "            field=\"gen_sum\"\n",
       "        },\n",
       "        color={\n",
       "            scale={\n",
       "                scheme=\"category10\"\n",
       "            },\n",
       "            field=\"resource\",\n",
       "            type=\"nominal\"\n",
       "        }\n",
       "    },\n",
       "    data={\n",
       "        values=...\n",
       "    }\n",
       ")"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sol_commit = innerjoin(solution.commit, \n",
    "                    gen_df[!, [:r_id, :resource]], \n",
    "                    on = :r_id)\n",
    "sol_commit = combine(groupby(sol_commit, [:resource, :hour]), \n",
    "            :gen => sum)\n",
    "sol_commit.hour = sol_commit.hour .- T_period[1]\n",
    "\n",
    "sol_commit |>\n",
    "@vlplot(:area, \n",
    "    x=:hour, y={:gen_sum, stack=:zero}, \n",
    "    color={\"resource:n\", scale={scheme=\"category10\"}})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A case involving more large coal or nuclear units with slower ramping limits than gas turbines or combined cycle plants might find ramp constraints more limiting. As in many cases, the impact of constraints is case dependent, and modelers must exercise some judicious application of domain knowledge (and experimentation with alternative formulations) to decide how complex your model should be to reflect important *binding* constraints that actually shape your outcomes of interest. Where constraints are non-binding or second order, it may be more practical to omit them entirely, reducing the computational intensity (solve time) of your model..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unit commitment with ramping and reserves\n",
    "\n",
    "We now add spinning reserve requirements to the model. Spinning reserves refer to generation capacity that is online and able to generate (e.g., within 10-30 minutes) if needed by the system operator. (Note: in Europe, these are referred to as 'replacement reserves' or formerly 'tertiary reserves.') The SO will establish reserve requirements to maintain sufficient capacity to respond to demand or supply forecast errors or in case of \"contingencies,\" such as the unplanned and sudden loss of a generating station or a transmission line. The SO then typically operates a reserve market to competitively procure this available capacity. Most SO's actually define several classes of reserve products defined by their response time and period over which they may be activated. \n",
    "\n",
    "Here we will focus on spinning reserve requirements and establish a simple set of reserve requirements for reserves up (ability to quickly increase output) and reserves down (ability to quickly reduce output):\n",
    "\n",
    "$$\n",
    "\\begin{align}\n",
    " & ResReqUp_t = 300 MW + 5\\% \\times Demand_t  &\\forall \\quad t \\in T \\\\\n",
    " & ResReqDn_t = 5\\% \\times Demand_t & \\forall \\quad t \\in T\n",
    "\\end{align}\n",
    "$$\n",
    "\n",
    "Here, $300 MW$ is our contigency reserves, meant to ensure we have sufficient upwards ramping capability online and available to cover the unexpected loss of 300 MW worth of generation. \n",
    "\n",
    "The 5% of demand term in the constraints above is meant to provide sufficient reserves in either upwards or downwards direction to cover errors in the demand forecast. For simplicity, we ignore solar PV and wind production in our reserve calculation, though in practice, we would want to consider solar and wind forecast errors in calculating up reserve requirements as well.\n",
    "\n",
    "In our simple system, only thermal generators provide reserves. (This can be easily adjusted by changing the sets and defining the potential reserve contributions for different sets of resources differently, such as storage or hydro resources). The contribution of each generators to meeting reserves and the overall reserve constraint are thus given by:\n",
    "\n",
    "$$\n",
    "\\begin{align}\n",
    " & RESUP_{g,t} \\leq Pmax_{g,t}COMMIT_{g,t} - GEN_{g,t} & \\forall \\quad g \\in G_{thermal} , t \\in T \\\\\n",
    " & RESDN_{g,t} \\leq GEN_{g,t} - Pmin_{g,t}COMMIT_{g,t} & \\forall \\quad g \\in G_{thermal} , t \\in T \\\\\n",
    " & RESUP_{g,t} \\leq RampUp_{g} & \\forall \\quad g \\in G_{thermal}, t \\in T\\\\ \n",
    " & RESDN_{g,t} \\leq RampDn_{g} & \\forall \\quad g \\in G_{thermal}, t \\in T \\\\\n",
    " & \\sum_{g \\in G_{thermal}} RESUP_{g,t} \\geq ResReqUp_t & \\forall \\quad t \\in T \\\\\n",
    " & \\sum_{g \\in G_{thermal}} RESDN_{g,t} \\geq ResReqDn_t & \\forall \\quad t \\in T\n",
    "\\end{align}\n",
    "$$\n",
    "\n",
    "We have added two new **decision variables**:\n",
    "\n",
    "- $RESUP_{g,t}$, up-reserve capacity (in MW) of generator $g$ at time $t$\n",
    "- $RESDN_{g,t}$, down-reserve capacity (in MW) of generator $g$ at time $t$\n",
    "\n",
    "Note that in this case, we constrain the reserve contribution for each thermal generator to be the same as their hourly ramp rates, $RampUp_{g}, RampDown_{g}$. In practice, reserve products typically require a faster response time, on the order of 10-30 minutes for \"tertiary\" reserves (aka spinning reserves or contingency reserves), and 5-15 minutes for \"secondary\" reserves (regulation reserves). Thus, depending on the reserve requirements being modeled, one might specify a distinct maximum reserve contribution for each unit that reflects their ramping capabilities over shorter time periods."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"img/reserves.png\" style=\"width: 450px; height: auto\" align=\"left\">\n",
    "\n",
    "<img src=\"img/reserves_taxonomy.png\" style=\"width: 450px; height: auto\" align=\"left\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Create solver function\n",
    "\n",
    "(We reuse steps 1 and 2 above to load packages and data.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "unit_commitment_full (generic function with 1 method)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#=\n",
    "Function to solve full unit commitment problem (commitment, ramp, reserve equations)\n",
    "Inputs:\n",
    "    gen_df -- dataframe with generator info\n",
    "    loads  -- load by time\n",
    "    gen_variable -- capacity factors of variable generators (in \"long\" format)\n",
    "    mip_gap -- desired relative MIP gap to pass to solver\n",
    "=#\n",
    "function unit_commitment_full(gen_df, loads, gen_variable, mip_gap)\n",
    "    UC = Model(HiGHS.Optimizer)\n",
    "    set_optimizer_attribute(UC, \"mip_rel_gap\", mip_gap)\n",
    "\n",
    "    # Define sets based on data\n",
    "    # Note the creation of several different sets of generators for use in\n",
    "    # different equations.\n",
    "    G_thermal = gen_df[gen_df[!,:up_time] .> 0,:r_id]\n",
    "    G_nonthermal = gen_df[gen_df[!,:up_time] .== 0,:r_id]\n",
    "    G_var = gen_df[gen_df[!,:is_variable] .== 1,:r_id] \n",
    "    G_nonvar = gen_df[gen_df[!,:is_variable] .== 0,:r_id]\n",
    "    G_nt_nonvar = intersect(G_nonvar, G_nonthermal)\n",
    "    G = gen_df.r_id\n",
    "    T = loads.hour\n",
    "    T_red = loads.hour[1:end-1]  # reduced time periods without last one\n",
    "\n",
    "    # Generator capacity factor time series for variable generators\n",
    "    gen_var_cf = innerjoin(gen_variable, \n",
    "                    gen_df[gen_df.is_variable .== 1 , \n",
    "                        [:r_id, :gen_full, :existing_cap_mw, :resource]], \n",
    "                    on = :gen_full)\n",
    "    gen_var_cf.max_gen = gen_var_cf.cf .* gen_var_cf.existing_cap_mw\n",
    "    \n",
    "    # Compute reserve requirements\n",
    "    ResReqUp = Dict(T[i] => 300  \n",
    "              + 0.05 * loads[loads.hour .== T[i],:demand][1]\n",
    "                    for i in 1:length(T))\n",
    "    ResReqDn = Dict(T[i] => 0\n",
    "              + 0.05 * loads[loads.hour .== T[i],:demand][1]                    \n",
    "                    for i in 1:length(T))\n",
    "    \n",
    "    # Decision variables   \n",
    "    @variables(UC, begin\n",
    "        GEN[G, T]  >= 0     # generation\n",
    "        GENAUX[G_thermal, T] >= 0 # auxiliary generation variable\n",
    "        COMMIT[G_thermal, T], Bin # commitment status (Bin=binary)\n",
    "        START[G_thermal, T], Bin  # startup decision\n",
    "        SHUT[G_thermal, T], Bin   # shutdown decision\n",
    "        RESUP[G_thermal, T]       # up reserve capacity\n",
    "        RESDN[G_thermal, T]       # down reserve capacity\n",
    "    end)\n",
    "                \n",
    "    # Objective function\n",
    "    @objective(UC, Min, \n",
    "        sum( (gen_df[gen_df.r_id .== i,:heat_rate_mmbtu_per_mwh][1] * gen_df[gen_df.r_id .== i,:fuel_cost][1] +\n",
    "            gen_df[gen_df.r_id .== i,:var_om_cost_per_mwh][1]) * GEN[i,t] \n",
    "                        for i in G_nonvar for t in T) + \n",
    "        sum(gen_df[gen_df.r_id .== i,:var_om_cost_per_mwh][1] * GEN[i,t] \n",
    "                        for i in G_var for t in T) + \n",
    "        sum(gen_df[gen_df.r_id .== i,:start_cost_per_mw][1] * \n",
    "            gen_df[gen_df.r_id .== i,:existing_cap_mw][1] *\n",
    "            START[i,t] \n",
    "                        for i in G_thermal for t in T)\n",
    "    )\n",
    "    \n",
    "    # Demand constraint\n",
    "    @constraint(UC, cDemand[t in T], \n",
    "        sum(GEN[i,t] for i in G) == loads[loads.hour .== t,:demand][1])\n",
    "\n",
    "    # Capacity constraints (thermal generators requiring commitment)\n",
    "    @constraint(UC, Cap_thermal_min[i in G_thermal, t in T], \n",
    "        GEN[i,t] >= COMMIT[i, t] * gen_df[gen_df.r_id .== i,:existing_cap_mw][1] *\n",
    "                        gen_df[gen_df.r_id .== i,:min_power][1])\n",
    "    @constraint(UC, Cap_thermal_max[i in G_thermal, t in T], \n",
    "        GEN[i,t] <= COMMIT[i, t] * gen_df[gen_df.r_id .== i,:existing_cap_mw][1])\n",
    "\n",
    "    # Capacity constraints (non-variable generation not requiring commitment)\n",
    "    @constraint(UC, Cap_nt_nonvar[i in G_nt_nonvar, t in T], \n",
    "        GEN[i,t] <= gen_df[gen_df.r_id .== i,:existing_cap_mw][1])\n",
    "\n",
    "    # Capacity constraints (variable generation)\n",
    "    @constraint(UC, Cap_var[i in 1:nrow(gen_var_cf)], \n",
    "            GEN[gen_var_cf[i,:r_id], gen_var_cf[i,:hour] ] <= \n",
    "                        gen_var_cf[i,:max_gen])\n",
    "    \n",
    "    # Unit commitment constraints\n",
    "    @constraint(UC, Startup[i in G_thermal, t in T],\n",
    "        COMMIT[i, t] >= sum(START[i, tt] \n",
    "                        for tt in intersect(T,\n",
    "                            (t-gen_df[gen_df.r_id .== i,:up_time][1]):t)))\n",
    "\n",
    "    @constraint(UC, Shutdown[i in G_thermal, t in T],\n",
    "        1-COMMIT[i, t] >= sum(SHUT[i, tt] \n",
    "                        for tt in intersect(T,\n",
    "                            (t-gen_df[gen_df.r_id .== i,:down_time][1]):t)))\n",
    "    \n",
    "    @constraint(UC, CommitmentStatus[i in G_thermal, t in T_red],\n",
    "        COMMIT[i,t+1] - COMMIT[i,t] == START[i,t+1] - SHUT[i,t+1])\n",
    "    \n",
    "    # Auxiliary variable\n",
    "    @constraint(UC, AuxGen[i in G_thermal, t in T],\n",
    "        GENAUX[i,t] == GEN[i,t] - COMMIT[i, t] * gen_df[gen_df.r_id .== i,:existing_cap_mw][1] *\n",
    "                        gen_df[gen_df.r_id .== i,:min_power][1])\n",
    "    \n",
    "    # Ramp equations (thermal generators)\n",
    "    @constraint(UC, RampUp_thermal[i in G_thermal, t in T_red], \n",
    "        GENAUX[i,t+1] - GENAUX[i,t] <= gen_df[gen_df.r_id .== i,:existing_cap_mw][1] * \n",
    "                                 gen_df[gen_df.r_id .== i,:ramp_up_percentage][1] )\n",
    "\n",
    "    @constraint(UC, RampDn_thermal[i in G_thermal, t in T_red], \n",
    "        GENAUX[i,t] - GENAUX[i,t+1] <= gen_df[gen_df.r_id .== i,:existing_cap_mw][1] * \n",
    "                                 gen_df[gen_df.r_id .== i,:ramp_dn_percentage][1] )\n",
    "\n",
    "    # Ramp equations (non-thermal generators)\n",
    "    @constraint(UC, RampUp_nonthermal[i in G_nonthermal, t in T_red], \n",
    "        GEN[i,t+1] - GEN[i,t] <= gen_df[gen_df.r_id .== i,:existing_cap_mw][1] * \n",
    "                                 gen_df[gen_df.r_id .== i,:ramp_up_percentage][1] )\n",
    "\n",
    "    @constraint(UC, RampDn[i in G, t in T_red], \n",
    "        GEN[i,t] - GEN[i,t+1] <= gen_df[gen_df.r_id .== i,:existing_cap_mw][1] * \n",
    "                                 gen_df[gen_df.r_id .== i,:ramp_dn_percentage][1] )\n",
    "      \n",
    "    # Reserve equations\n",
    "    # (1) Reserves limited by committed capacity of generator\n",
    "    @constraint(UC, ResUpCap[i in G_thermal, t in T],\n",
    "        RESUP[i,t] <= COMMIT[i, t] * gen_df[gen_df.r_id .== i,:existing_cap_mw][1]\n",
    "                        - GEN[i,t])\n",
    "\n",
    "    @constraint(UC, ResDnCap[i in G_thermal, t in T],\n",
    "        RESDN[i,t] <= GEN[i,t] - \n",
    "                        COMMIT[i, t] * gen_df[gen_df.r_id .== i,:existing_cap_mw][1] *\n",
    "                        gen_df[gen_df.r_id .== i,:min_power][1])\n",
    "\n",
    "    # (2) Reserves limited by ramp rates\n",
    "    @constraint(UC, ResUpRamp[i in G_thermal, t in T],\n",
    "        RESUP[i,t] <= gen_df[gen_df.r_id .== i,:existing_cap_mw][1] * \n",
    "                          gen_df[gen_df.r_id .== i,:ramp_up_percentage][1])\n",
    "\n",
    "    @constraint(UC, ResDnRamp[i in G_thermal, t in T],\n",
    "        RESDN[i,t] <= gen_df[gen_df.r_id .== i,:existing_cap_mw][1] * \n",
    "                          gen_df[gen_df.r_id .== i,:ramp_dn_percentage][1])\n",
    "\n",
    "    # (3) Overall reserve requirements\n",
    "    @constraint(UC, ResUpRequirement[t in T],\n",
    "        sum(RESUP[i,t] for i in G_thermal) >= \n",
    "                ResReqUp[t])\n",
    "\n",
    "    @constraint(UC, ResDnRequirement[t in T],\n",
    "        sum(RESDN[i,t] for i in G_thermal) >= \n",
    "                ResReqDn[t])\n",
    "\n",
    "    # Solve statement (! indicates runs in place)\n",
    "    optimize!(UC)\n",
    "\n",
    "    # Generation solution\n",
    "    gen = value_to_df_2dim(value.(GEN))\n",
    "\n",
    "    # Commitment status solution\n",
    "    commit = value_to_df_2dim(value.(COMMIT))\n",
    "\n",
    "    # Calculate curtailment\n",
    "    curtail = innerjoin(gen_var_cf, gen, on = [:r_id, :hour])\n",
    "    curtail.curt = curtail.cf .* curtail.existing_cap_mw - curtail.gen\n",
    "    \n",
    "    # Return the solution and objective as named tuple\n",
    "    return (\n",
    "        gen,\n",
    "        commit,\n",
    "        curtail,\n",
    "        cost = objective_value(UC),\n",
    "        status = termination_status(UC)\n",
    "    )\n",
    "\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. Solve the model and plot results\n",
    "\n",
    "**Note: this might take a little while depending on your machine.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running HiGHS 1.5.3 [date: 1970-01-01, git hash: 45a127b78]\n",
      "Copyright (c) 2023 HiGHS under MIT licence terms\n",
      "Presolving model\n",
      "5334 rows, 3761 cols, 16921 nonzeros\n",
      "3795 rows, 2750 cols, 13799 nonzeros\n",
      "2805 rows, 2588 cols, 13303 nonzeros\n",
      "2194 rows, 2004 cols, 12003 nonzeros\n",
      "2179 rows, 2000 cols, 11839 nonzeros\n",
      "\n",
      "Solving MIP model with:\n",
      "   2179 rows\n",
      "   2000 cols (1232 binary, 0 integer, 0 implied int., 768 continuous)\n",
      "   11839 nonzeros\n",
      "\n",
      "        Nodes      |    B&B Tree     |            Objective Bounds              |  Dynamic Constraints |       Work      \n",
      "     Proc. InQueue |  Leaves   Expl. | BestBound       BestSol              Gap |   Cuts   InLp Confl. | LpIters     Time\n",
      "\n",
      "         0       0         0   0.00%   -16834.579667   inf                  inf        0      0      0         0     0.1s\n",
      "         0       0         0   0.00%   897185.423847   inf                  inf        0      0      0       644     0.1s\n",
      " C       0       0         0   0.00%   899517.186185   915532.494331      1.75%     1284     49     28       791     0.2s\n",
      "\n",
      "Solving report\n",
      "  Status            Optimal\n",
      "  Primal bound      915532.494331\n",
      "  Dual bound        899517.186185\n",
      "  Gap               1.75% (tolerance: 2%)\n",
      "  Solution status   feasible\n",
      "                    915532.494331 (objective)\n",
      "                    0 (bound viol.)\n",
      "                    0 (int. viol.)\n",
      "                    0 (row viol.)\n",
      "  Timing            0.22 (total)\n",
      "                    0.05 (presolve)\n",
      "                    0.00 (postsolve)\n",
      "  Nodes             1\n",
      "  LP iterations     791 (total)\n",
      "                    0 (strong br.)\n",
      "                    147 (separation)\n",
      "                    0 (heuristics)\n"
     ]
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text-anchor=\"end\" transform=\"translate(-7,60.14285714285714)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">2,500</text><text text-anchor=\"end\" transform=\"translate(-7,31.57142857142858)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">3,000</text><text text-anchor=\"end\" transform=\"translate(-7,3)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">3,500</text></g><g class=\"mark-rule role-axis-domain\" pointer-events=\"none\"><line transform=\"translate(0,200)\" x2=\"0\" y2=\"-200\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"/></g><g class=\"mark-text role-axis-title\" pointer-events=\"none\"><text text-anchor=\"middle\" transform=\"translate(-36.0244140625,100) rotate(-90) translate(0,-2)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">gen_sum</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g><g class=\"mark-group role-scope pathgroup\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 21.4; resource: biomass\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,117.228L8.333,121.142L16.667,120.017L25,116.671L33.333,105.758L41.667,95.221L50,85.538L58.333,98.823L66.667,143.094L75,150.097L83.333,148.744L91.667,156.626L100,157.255L108.333,157.475L116.667,157.726L125,158L133.333,158.172L141.667,133.737L150,76.843L158.333,60.778L166.667,61.092L175,76.642L183.333,93.809L191.667,107.863L191.667,109.086L183.333,95.032L175,77.865L166.667,62.314L158.333,62.001L150,78.066L141.667,134.96L133.333,158.172L125,158L116.667,157.726L108.333,157.475L100,157.255L91.667,156.626L83.333,149.967L75,151.32L66.667,144.317L58.333,100.046L50,86.761L41.667,96.444L33.333,106.981L25,117.894L16.667,121.24L8.333,122.364L0,118.451Z\" fill=\"#8c564b\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 42; resource: hydroelectric_pumped_storage\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,118.451L8.333,122.364L16.667,121.24L25,117.894L33.333,106.981L41.667,96.444L50,86.761L58.333,100.046L66.667,144.317L75,151.32L83.333,149.967L91.667,156.626L100,157.255L108.333,157.475L116.667,157.726L125,158L133.333,158.172L141.667,134.96L150,78.066L158.333,62.001L166.667,62.314L175,77.865L183.333,95.032L191.667,109.086L191.667,111.486L183.333,97.432L175,80.265L166.667,64.714L158.333,64.401L150,80.466L141.667,137.36L133.333,158.172L125,158L116.667,157.726L108.333,157.475L100,157.255L91.667,156.626L83.333,152.367L75,153.72L66.667,146.717L58.333,102.446L50,89.161L41.667,98.844L33.333,109.381L25,120.294L16.667,123.64L8.333,124.764L0,120.851Z\" fill=\"#e377c2\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 1217.282468; resource: natural_gas_fired_combined_cycle\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,120.851L8.333,124.764L16.667,123.64L25,120.294L33.333,109.381L41.667,98.844L50,89.161L58.333,102.446L66.667,146.717L75,153.72L83.333,152.367L91.667,156.626L100,157.255L108.333,157.475L116.667,157.726L125,158L133.333,158.172L141.667,137.36L150,80.466L158.333,64.401L166.667,64.714L175,80.265L183.333,97.432L191.667,111.486L191.667,191.042L183.333,186.945L175,171.265L166.667,155.714L158.333,155.401L150,171.466L141.667,200L133.333,200L125,200L116.667,200L108.333,200L100,200L91.667,200L83.333,200L75,200L66.667,197.868L58.333,194.17L50,187.117L41.667,185.209L33.333,192.43L25,192.43L16.667,192.43L8.333,192.43L0,190.41Z\" fill=\"#7f7f7f\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 167.8238; resource: natural_gas_fired_combustion_turbine\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,190.41L8.333,192.43L16.667,192.43L25,192.43L33.333,192.43L41.667,185.209L50,187.117L58.333,194.17L66.667,197.868L75,200L83.333,200L91.667,200L100,200L108.333,200L116.667,200L125,200L133.333,200L141.667,200L150,171.466L158.333,155.401L166.667,155.714L175,171.265L183.333,186.945L191.667,191.042L191.667,200L183.333,200L175,200L166.667,200L158.333,200L150,200L141.667,200L133.333,200L125,200L116.667,200L108.333,200L100,200L91.667,200L83.333,200L75,200L66.667,200L58.333,200L50,200L41.667,200L33.333,200L25,200L16.667,200L8.333,200L0,200Z\" fill=\"#bcbd22\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 163.3088; resource: _onshore_wind_turbine\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" 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role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 0; resource: _solar_photovoltaic\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,117.228L8.333,121.142L16.667,120.017L25,116.671L33.333,105.758L41.667,95.221L50,72.582L58.333,47.023L66.667,31.199L75,15.219L83.333,7.259L91.667,12.798L100,21.157L108.333,25.526L116.667,31.288L125,38.646L133.333,48.573L141.667,57.923L150,65.667L158.333,60.778L166.667,61.092L175,76.642L183.333,93.809L191.667,107.863L191.667,107.863L183.333,93.809L175,76.642L166.667,61.092L158.333,60.778L150,75.207L141.667,122.643L133.333,142.133L125,138.475L116.667,136.328L108.333,135.343L100,135.154L91.667,135.578L83.333,128.039L75,130.359L66.667,126.719L58.333,91.243L50,83.642L41.667,95.221L33.333,105.758L25,116.671L16.667,120.017L8.333,121.142L0,117.228Z\" fill=\"#d62728\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 0; resource: _solar_photovoltaic_btm\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,117.228L8.333,121.142L16.667,120.017L25,116.671L33.333,105.758L41.667,95.221L50,83.642L58.333,91.243L66.667,126.719L75,130.359L83.333,128.039L91.667,135.578L100,135.154L108.333,135.343L116.667,136.328L125,138.475L133.333,142.133L141.667,122.643L150,75.207L158.333,60.778L166.667,61.092L175,76.642L183.333,93.809L191.667,107.863L191.667,107.863L183.333,93.809L175,76.642L166.667,61.092L158.333,60.778L150,76.843L141.667,133.737L133.333,158.172L125,158L116.667,157.726L108.333,157.475L100,157.255L91.667,156.626L83.333,148.744L75,150.097L66.667,143.094L58.333,98.823L50,85.538L41.667,95.221L33.333,105.758L25,116.671L16.667,120.017L8.333,121.142L0,117.228Z\" fill=\"#9467bd\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 0; resource: _curtailment\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,107.714L8.333,111.257L16.667,113.257L25,110.743L33.333,100.971L41.667,87.086L50,68.161L58.333,44.019L66.667,21.454L75,7.519L83.333,0.723L91.667,7.353L100,3.075L108.333,2.364L116.667,8.514L125,20.655L133.333,45.123L141.667,53.248L150,62.479L158.333,57.086L166.667,56.8L175,70.971L183.333,86.4L191.667,99.429L191.667,99.429L183.333,86.4L175,70.971L166.667,56.8L158.333,57.086L150,62.479L141.667,53.248L133.333,45.561L125,38.646L116.667,31.288L108.333,25.526L100,21.157L91.667,9.638L83.333,0.723L75,7.519L66.667,21.454L58.333,44.019L50,68.161L41.667,87.086L33.333,100.971L25,110.743L16.667,113.257L8.333,111.257L0,107.714Z\" fill=\"#1f77b4\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g></g><g class=\"mark-group role-legend\" role=\"graphics-symbol\" aria-roledescription=\"legend\" aria-label=\"Symbol legend titled 'resource' for fill color with 9 values: _curtailment, _onshore_wind_turbine, _small_hydroelectric, _solar_photovoltaic, _solar_photovoltaic_btm, ending with natural_gas_fired_combustion_turbine\"><g transform=\"translate(218,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h174v131h-174Z\" pointer-events=\"none\"/><g><g class=\"mark-group role-legend-entry\"><g transform=\"translate(0,16)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"/><g><g class=\"mark-group role-scope\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#1f77b4\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_curtailment</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,13)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#ff7f0e\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_onshore_wind_turbine</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,26)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#2ca02c\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_small_hydroelectric</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,39)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#d62728\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_solar_photovoltaic</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,52)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#9467bd\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">_solar_photovoltaic_btm</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,65)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#8c564b\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">biomass</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,78)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#e377c2\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">hydroelectric_pumped_storage</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,91)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#7f7f7f\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">natural_gas_fired_combined_cycle</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,104)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#bcbd22\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">natural_gas_fired_combustion_tu…</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g><g class=\"mark-text role-legend-title\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(0,9)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">resource</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g></g></g></svg>"
      ],
      "text/plain": [
       "@vlplot(\n",
       "    mark=\"area\",\n",
       "    encoding={\n",
       "        x={\n",
       "            field=\"hour\"\n",
       "        },\n",
       "        y={\n",
       "            stack=\"zero\",\n",
       "            field=\"gen_sum\"\n",
       "        },\n",
       "        color={\n",
       "            scale={\n",
       "                scheme=\"category10\"\n",
       "            },\n",
       "            field=\"resource\",\n",
       "            type=\"nominal\"\n",
       "        }\n",
       "    },\n",
       "    data={\n",
       "        values=...\n",
       "    }\n",
       ")"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solution = unit_commitment_full(gen_df_sens, loads_multi, gen_variable_multi, 0.02);\n",
    " # To keep solve times to a few minutes, we increase the MIP gap tolerance\n",
    " # in this more complex case to 2% (mip_gap=0.02). You can play with this setting to see \n",
    " # how the MIP gap affects solve times on your computer.\n",
    "   \n",
    "\n",
    "# Add in BTM solar and curtailment and plot results\n",
    "\n",
    "sol_gen = innerjoin(solution.gen, \n",
    "                    gen_df[!, [:r_id, :resource]], \n",
    "                    on = :r_id)\n",
    "sol_gen = combine(groupby(sol_gen, [:resource, :hour]), \n",
    "            :gen => sum)\n",
    "\n",
    "# Rename generators (for plotting purposes)\n",
    "sol_gen[sol_gen.resource .== \"solar_photovoltaic\", :resource] .= \"_solar_photovoltaic\"\n",
    "sol_gen[sol_gen.resource .== \"onshore_wind_turbine\", :resource] .= \"_onshore_wind_turbine\"\n",
    "sol_gen[sol_gen.resource .== \"small_hydroelectric\", :resource] .= \"_small_hydroelectric\"\n",
    "\n",
    "# BTM solar\n",
    "btm = DataFrame(resource = repeat([\"_solar_photovoltaic_btm\"]; outer=length(T_period)), \n",
    "    hour = T_period,\n",
    "    gen_sum = gen_variable_multi[gen_variable_multi.gen_full .== \"wec_sdge_solar_photovoltaic_1.0\",:cf] * 600)\n",
    "append!(sol_gen, btm)\n",
    "\n",
    "# Curtailment\n",
    "curtail = combine(groupby(solution.curtail, [:hour]),\n",
    "            :curt => sum)\n",
    "curtail[!, :resource] .= \"_curtailment\"\n",
    "rename!(curtail, :curt_sum => :gen_sum)\n",
    "append!(sol_gen, curtail[:,[:resource, :hour, :gen_sum]])\n",
    "\n",
    "# Rescale hours\n",
    "sol_gen.hour = sol_gen.hour .- T_period[1]\n",
    "\n",
    "sol_gen |>\n",
    "@vlplot(:area, \n",
    "    x=:hour, y={:gen_sum, stack=:zero}, \n",
    "    color={\"resource:n\", scale={scheme=\"category10\"}})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now see that the need to maintain reserve requirements leads to greater commitment of natural gas units throughout the day. The addition of CCGTs and GTs to meet reserve requirements leads to greater curtailment of wind and solar in the afternoon hours. We also see more CT units committed during the morning ramp as well as the afternoon hours to help provide reserves."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
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font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">20</text></g><g class=\"mark-rule role-axis-domain\" pointer-events=\"none\"><line transform=\"translate(0,0)\" x2=\"200\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"/></g><g class=\"mark-text role-axis-title\" pointer-events=\"none\"><text text-anchor=\"middle\" transform=\"translate(100,30)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">hour</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g><g class=\"mark-group role-axis\" role=\"graphics-symbol\" aria-roledescription=\"axis\" aria-label=\"Y-axis titled 'gen_sum' for a linear scale with values from 0 to 20\"><g transform=\"translate(0.5,0.5)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"/><g><g class=\"mark-rule role-axis-tick\" pointer-events=\"none\"><line transform=\"translate(0,200)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"/><line transform=\"translate(0,150)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"/><line transform=\"translate(0,100)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"/><line transform=\"translate(0,50)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"/><line transform=\"translate(0,0)\" x2=\"-5\" y2=\"0\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"/></g><g class=\"mark-text role-axis-label\" pointer-events=\"none\"><text text-anchor=\"end\" transform=\"translate(-7,203)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">0</text><text text-anchor=\"end\" transform=\"translate(-7,153)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">5</text><text text-anchor=\"end\" transform=\"translate(-7,103)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">10</text><text text-anchor=\"end\" transform=\"translate(-7,53)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">15</text><text text-anchor=\"end\" transform=\"translate(-7,3)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">20</text></g><g class=\"mark-rule role-axis-domain\" pointer-events=\"none\"><line transform=\"translate(0,200)\" x2=\"0\" y2=\"-200\" stroke=\"#888\" stroke-width=\"1\" opacity=\"1\"/></g><g class=\"mark-text role-axis-title\" pointer-events=\"none\"><text text-anchor=\"middle\" transform=\"translate(-22.123046875,100) rotate(-90) translate(0,-2)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">gen_sum</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g><g class=\"mark-group role-scope pathgroup\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 6; resource: natural_gas_fired_combined_cycle\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,90L8.333,100L16.667,100L25,100L33.333,100L41.667,80L50,90L58.333,110L66.667,140L75,150L83.333,150L91.667,150L100,150L108.333,150L116.667,150L125,150L133.333,150L141.667,150L150,50L158.333,0L166.667,0L175,50L183.333,80L191.667,100L191.667,150L183.333,130L175,100L166.667,50L158.333,50L150,100L141.667,200L133.333,200L125,200L116.667,200L108.333,200L100,200L91.667,200L83.333,200L75,200L66.667,190L58.333,170L50,150L41.667,140L33.333,160L25,160L16.667,160L8.333,160L0,150Z\" fill=\"#1f77b4\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h200v200h-200Z\"/><g><g class=\"mark-area role-mark marks\" role=\"graphics-object\" aria-roledescription=\"area mark container\"><path aria-label=\"hour: 0; gen_sum: 5; resource: natural_gas_fired_combustion_turbine\" role=\"graphics-symbol\" aria-roledescription=\"area mark\" d=\"M0,150L8.333,160L16.667,160L25,160L33.333,160L41.667,140L50,150L58.333,170L66.667,190L75,200L83.333,200L91.667,200L100,200L108.333,200L116.667,200L125,200L133.333,200L141.667,200L150,100L158.333,50L166.667,50L175,100L183.333,130L191.667,150L191.667,200L183.333,200L175,200L166.667,200L158.333,200L150,200L141.667,200L133.333,200L125,200L116.667,200L108.333,200L100,200L91.667,200L83.333,200L75,200L66.667,200L58.333,200L50,200L41.667,200L33.333,200L25,200L16.667,200L8.333,200L0,200Z\" fill=\"#ff7f0e\"/></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g></g><g class=\"mark-group role-legend\" role=\"graphics-symbol\" aria-roledescription=\"legend\" aria-label=\"Symbol legend titled 'resource' for fill color with 2 values: natural_gas_fired_combined_cycle, natural_gas_fired_combustion_turbine\"><g transform=\"translate(218,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h174v40h-174Z\" pointer-events=\"none\"/><g><g class=\"mark-group role-legend-entry\"><g transform=\"translate(0,16)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h0v0h0Z\" pointer-events=\"none\"/><g><g class=\"mark-group role-scope\" role=\"graphics-object\" aria-roledescription=\"group mark container\"><g transform=\"translate(0,0)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#1f77b4\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">natural_gas_fired_combined_cycle</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g><g transform=\"translate(0,13)\"><path class=\"background\" aria-hidden=\"true\" d=\"M0,0h173.8759765625v11h-173.8759765625Z\" pointer-events=\"none\" opacity=\"1\"/><g><g class=\"mark-symbol role-legend-symbol\" pointer-events=\"none\"><path transform=\"translate(6,6)\" d=\"M5,0A5,5,0,1,1,-5,0A5,5,0,1,1,5,0\" fill=\"#ff7f0e\" stroke-width=\"1.5\" opacity=\"1\"/></g><g class=\"mark-text role-legend-label\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(16,9)\" font-family=\"sans-serif\" font-size=\"10px\" fill=\"#000\" opacity=\"1\">natural_gas_fired_combustion_tu…</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g><g class=\"mark-text role-legend-title\" pointer-events=\"none\"><text text-anchor=\"start\" transform=\"translate(0,9)\" font-family=\"sans-serif\" font-size=\"11px\" font-weight=\"bold\" fill=\"#000\" opacity=\"1\">resource</text></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" pointer-events=\"none\" display=\"none\"/></g></g></g><path class=\"foreground\" aria-hidden=\"true\" d=\"\" display=\"none\"/></g></g></g></svg>"
      ],
      "text/plain": [
       "@vlplot(\n",
       "    mark=\"area\",\n",
       "    encoding={\n",
       "        x={\n",
       "            field=\"hour\"\n",
       "        },\n",
       "        y={\n",
       "            stack=\"zero\",\n",
       "            field=\"gen_sum\"\n",
       "        },\n",
       "        color={\n",
       "            scale={\n",
       "                scheme=\"category10\"\n",
       "            },\n",
       "            field=\"resource\",\n",
       "            type=\"nominal\"\n",
       "        }\n",
       "    },\n",
       "    data={\n",
       "        values=...\n",
       "    }\n",
       ")"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sol_commit = innerjoin(solution.commit, \n",
    "                    gen_df[!, [:r_id, :resource]], \n",
    "                    on = :r_id)\n",
    "sol_commit = combine(groupby(sol_commit, [:resource, :hour]), \n",
    "            :gen => sum)\n",
    "sol_commit.hour = sol_commit.hour .- T_period[1]\n",
    "\n",
    "sol_commit |>\n",
    "@vlplot(:area, \n",
    "    x=:hour, y={:gen_sum, stack=:zero}, \n",
    "    color={\"resource:n\", scale={scheme=\"category10\"}})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Further resources\n",
    "\n",
    "Knueven, B., Ostrowski, J., & Watson, J.-P. (2019). On Mixed Integer Programming Formulations for the Unit Commitment Problem. Optimization Online, 91. http://www.optimization-online.org/DB_FILE/2018/11/6930.pdf\n",
    "\n",
    "Morales-Espana, G., Latorre, J. M., & Ramos, A. (2013). Tight and Compact MILP Formulation of Start-Up and Shut-Down Ramping in Unit Commitment. IEEE Transactions on Power Systems, 28(2), 1288–1296. https://doi.org/10.1109/TPWRS.2012.2222938\n",
    "\n",
    "Morales-España, G., Ramírez-Elizondo, L., & Hobbs, B. F. (2017). Hidden power system inflexibilities imposed by traditional unit commitment formulations. Applied Energy, 191, 223–238. https://doi.org/10.1016/j.apenergy.2017.01.089\n",
    "\n",
    "Ostrowski, J., Anjos, M. F., & Vannelli, A. (2012). Tight Mixed Integer Linear Programming Formulations for the Unit Commitment Problem. IEEE Transactions on Power Systems, 27(1), 39–46. https://doi.org/10.1109/TPWRS.2011.2162008"
   ]
  }
 ],
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