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use policies in amiris
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@maurerle
maurerle committed Jan 22, 2024
1 parent 12c4f0f commit 4fb86b6
Showing 1 changed file with 125 additions and 18 deletions.
143 changes: 125 additions & 18 deletions assume/scenario/loader_amiris.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,19 +2,18 @@
#
# SPDX-License-Identifier: AGPL-3.0-or-later

import calendar
import logging
from datetime import datetime, timedelta
from datetime import timedelta

import dateutil.rrule as rr
import numpy as np
import pandas as pd
import yaml
from tqdm import tqdm
from yamlinclude import YamlIncludeConstructor

from assume.common.base import LearningConfig
from assume.common.forecasts import CsvForecaster, Forecaster, NaiveForecast
from assume.common.forecasts import NaiveForecast
from assume.common.market_objects import MarketConfig, MarketProduct
from assume.strategies.extended import SupportStrategy
from assume.world import World

logger = logging.getLogger(__name__)
Expand Down Expand Up @@ -51,7 +50,20 @@ def read_csv(base_path, filename):
)["load"]


def get_send_receive_msgs_per_id(agent_id, contracts_config: list):
def get_send_receive_msgs_per_id(agent_id: int, contracts_config: list[dict]):
"""
AMIRIS contract conversion function which finds the list of ids which receive or send a message from/to the agent with agent_id.
Args:
agent_id (int): the agent id to which the contracts are found
contracts_config (list[dict]): whole contracts dict read from yaml
Returns:
tuple: A tuple containing the following:
- list: A list containing the ids of sending agents.
- list: A list containing the ids of receiving agents
"""

sends = []
receives = []
for contracts in contracts_config:
Expand Down Expand Up @@ -121,8 +133,46 @@ def add_agent_to_world(
contracts: list,
base_path: str,
markups: dict = {},
supports: dict = {},
):
"""
Adds an agent from a amiris agent definition to the ASSUME world.
It should be called in load_amiris_async, which loads agents in the correct order.
Args:
agent (dict): AMIRIS agent dict
world (World): ASSUME world to add the agent to
prices (dict): prices read from amiris scenario beforehand
contracts (list): contracts read from the amiris scenario beforehand
base_path (str): base path to load profile csv files from
markups (dict, optional): markups read from former agents. Defaults to {}.
"""
match agent["Type"]:
case "SupportPolicy":
support_data = agent["Attributes"]["SetSupportData"]
supports |= {x.pop("Set"): x for x in support_data}
world.add_unit_operator(agent["Id"])

for name, support in supports.items():
contract = list(support.keys())[0]
value = list(support[contract].values())[0]
# TODO
world.add_unit(
f"{name}_{agent['Id']}",
"demand",
agent["Id"],
{
"min_power": 0,
"max_power": 100000,
"bidding_strategies": {
"energy": "support",
"financial_support": "support",
},
"technology": "demand",
"price": value,
},
NaiveForecast(world.index, demand=100000),
)
case "EnergyExchange" | "DayAheadMarketSingleZone":
market_config = MarketConfig(
name=f"Market_{agent['Id']}",
Expand All @@ -140,6 +190,28 @@ def add_agent_to_world(
)
world.add_market_operator(f"Market_{agent['Id']}")
world.add_market(f"Market_{agent['Id']}", market_config)

if supports:
support_config = MarketConfig(
name=f"SupportMarket_{agent['Id']}",
opening_hours=rr.rrule(rr.YEARLY, dtstart=start, until=end),
opening_duration=timedelta(hours=1),
market_mechanism="pay_as_bid_contract",
market_products=[
MarketProduct(rd(months=12), 1, timedelta(hours=1))
],
additional_fields=[
"sender_id",
"contract", # one of MPVAR, MPFIX, CFD
"eligible_lambda",
"evaluation_frequency", # monthly
],
product_type="financial_support",
supports_get_unmatched=True,
maximum_bid_volume=1e6,
)
world.add_market_operator(f"SupportMarket_{agent['Id']}")
world.add_market(f"SupportMarket_{agent['Id']}", support_config)
case "CarbonMarket":
co2_price = agent["Attributes"]["Co2Prices"]
if isinstance(co2_price, str):
Expand Down Expand Up @@ -182,7 +254,10 @@ def add_agent_to_world(
world.add_unit_operator(operator_id)
device = agent["Attributes"]["Device"]
strategy = agent["Attributes"]["Strategy"]
if strategy["StrategistType"] != "SINGLE_AGENT_MIN_SYSTEM_COST":
if strategy["StrategistType"] not in [
"SINGLE_AGENT_MIN_SYSTEM_COST",
"SINGLE_AGENT_MAX_PROFIT",
]:
logger.warning(f"unknown strategy for storage trader: {strategy}")

forecast_price = prices.get("co2", 20)
Expand Down Expand Up @@ -222,6 +297,7 @@ def add_agent_to_world(
case "NoSupportTrader":
# does not get support - just trades renewables
# has a ShareOfRevenues (how much of the profit he keeps)
# can also have a ForecastError
world.add_unit_operator(f"Operator_{agent['Id']}")
case "SystemOperatorTrader":
world.add_unit_operator(f"Operator_{agent['Id']}")
Expand All @@ -234,12 +310,16 @@ def add_agent_to_world(
max_markup = agent["Attributes"]["maxMarkup"]
markups[agent["Id"]] = (min_markup, max_markup)
case "PredefinedPlantBuilder":
# this is the actual powerplant
# this is the actual powerplant/PlantBuilder
prototype = agent["Attributes"]["Prototype"]
attr = agent["Attributes"]
# first get send and receives for our PlantBuilder
send, receive = get_send_receive_msgs_per_id(agent["Id"], contracts)
# the first multi send includes message from us to our operator/portfolio
raw_operator_id = get_matching_send_one_or_multi(agent["Id"], send[0])
# we need to find send and receive for the raw operator too
send_t, receive_t = get_send_receive_msgs_per_id(raw_operator_id, contracts)
# the third entry here is the multi send to the actual trader
raw_trader_id = get_matching_send_one_or_multi(raw_operator_id, send_t[2])
operator_id = f"Operator_{raw_operator_id}"
fuel_price = prices.get(translate_fuel_type[prototype["FuelType"]], 0)
Expand All @@ -254,6 +334,7 @@ def add_agent_to_world(
)
# TODO UnplannedAvailabilityFactor is not respected

# we get the markups from the trader id:
min_markup, max_markup = markups.get(raw_trader_id, (0, 0))
# Amiris interpolates blocks linearly
interpolated_values = interpolate_blocksizes(
Expand Down Expand Up @@ -309,19 +390,37 @@ def add_agent_to_world(
fuel_price=fuel_price,
co2_price=prices.get("co2", 0),
)
# TODO attr["SupportInstrument"] and
strategies = {"energy": "naive"}
support_instrument = attr.get("SupportInstrument")
support_conf = supports.get(attr.get("Set"))
bidding_params = {}
if support_instrument and support_conf:
strategies["financial_support"] = "support"
if support_instrument == "FIT":
conf_key = "TsFit"
elif support_instrument in ["CFD", "MPVAR"]:
conf_key = "Lcoe"
else:
conf_key = "Premium"
value = support_conf[support_instrument][conf_key]
bidding_params["contract_types"] = support_instrument
bidding_params["support_value"] = value
# ASSUME evaluates contracts on a monthly schedule
bidding_params["evaluation_frequency"] = rr.MONTHLY

world.add_unit(
f"VariableRenewableOperator_{agent['Id']}",
"power_plant",
operator_id,
{
"min_power": 0,
"max_power": max_power,
"bidding_strategies": {"energy": "naive"},
"bidding_strategies": strategies,
"technology": translate_fuel_type[attr["EnergyCarrier"]],
"fuel_type": translate_fuel_type[attr["EnergyCarrier"]],
"emission_factor": 0,
"efficiency": 1,
"bidding_params": bidding_params,
},
forecast,
)
Expand All @@ -343,17 +442,22 @@ async def load_amiris_async(
study_case: str,
base_path: str,
):
"""
Loads an Amiris scenario
Args:
world (World): the ASSUME world
scenario (str): the scenario name
study_case (str): study case to define
base_path (str): base path from where to load the amrisi scenario
"""
amiris_scenario = read_amiris_yaml(base_path)
# DeliveryIntervalInSteps = 3600
# In practice - this seems to be a fixed number in AMIRIS
if study_case.lower() == "simple":
print("is simple - adjusting start time")
amiris_scenario["GeneralProperties"]["Simulation"][
"StartTime"
] = "2020-12-31_23:58:00"

start = amiris_scenario["GeneralProperties"]["Simulation"]["StartTime"]
start = pd.to_datetime(start, format="%Y-%m-%d_%H:%M:%S")
if calendar.isleap(start.year):
start += timedelta(days=1)
end = amiris_scenario["GeneralProperties"]["Simulation"]["StopTime"]
end = pd.to_datetime(end, format="%Y-%m-%d_%H:%M:%S")
# AMIRIS caveat: start and end is always two minutes before actual start
Expand All @@ -362,6 +466,7 @@ async def load_amiris_async(
save_interval = amiris_scenario["GeneralProperties"]["Output"]["Interval"] // 2
prices = {}
index = pd.date_range(start=start, end=end, freq="1h", inclusive="left")
world.bidding_strategies["support"] = SupportStrategy
await world.setup(
start=start,
end=end,
Expand All @@ -371,11 +476,13 @@ async def load_amiris_async(
)
# helper dict to map trader markups/markdowns to powerplants
markups = {}
supports = {}
keyorder = [
"EnergyExchange",
"DayAheadMarketSingleZone",
"CarbonMarket",
"FuelsMarket",
"SupportPolicy",
"DemandTrader",
"StorageTrader",
"RenewableTrader",
Expand All @@ -387,7 +494,6 @@ async def load_amiris_async(
"VariableRenewableOperator",
"Biogas",
"MeritOrderForecaster",
"SupportPolicy",
]
agents_sorted = sorted(
amiris_scenario["Agents"], key=lambda agent: keyorder.index((agent["Type"]))
Expand All @@ -400,6 +506,7 @@ async def load_amiris_async(
amiris_scenario["Contracts"],
base_path,
markups,
supports,
)
# calculate market price before simulation
world
Expand All @@ -409,7 +516,7 @@ async def load_amiris_async(
# To use this with amiris run:
# git clone https://gitlab.com/dlr-ve/esy/amiris/examples.git amiris-examples
# next to the assume folder
scenario = "Simple" # Germany2019 or Austria2019 or Simple
scenario = "Germany2019" # Germany2019 or Austria2019 or Simple
base_path = f"../amiris-examples/{scenario}/"
amiris_scenario = read_amiris_yaml(base_path)
sends, receives = get_send_receive_msgs_per_id(
Expand Down

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