add internal load computation

LBNL-ETA · Apr 4, 2024 · 2ad3a6b · 2ad3a6b
1 parent 74ecd07
commit 2ad3a6b
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Showing 4 changed files with 37 additions and 20 deletions.
diff --git a/README.md b/README.md
@@ -147,11 +147,11 @@ These full list of outputs is here:
     - `termination`: Status of optimization indicating whether the solver has reached an optimal solution, as string.
 
 
-The `output-data` is a special entry as it contains time series data for all the inputs and outputs of the optimization process. It is not necessary for a general user to understand these, but might be important for developers or debugging. The `output-data` can be formatted into a pandas dataframe and subsequently easily plotted and analyzed:
+The `output-data` is a special entry as it contains time series data for all the inputs and outputs of the optimization process. It is not necessary for a general user to understand these, but might be important for developers or for debugging. The `output-data` can be formatted into a pandas dataframe and subsequently easily plotted and analyzed:
 
 ```python
 # convert df_outputs to pandas
-df = pd.DataFrame(ctrl.get_output(keys=['output-data'])['output-data'])
+df = pd.read_json(io.StringIO(ctrl.get_output(keys=['output-data'])['output-data']))
 df.index = pd.to_datetime(df.index, unit='ms')
 
 # make exmaple plot of results

diff --git a/afc/ctrlWrapper.py b/afc/ctrlWrapper.py
@@ -12,6 +12,7 @@
 # pylint: disable=too-many-branches, too-many-statements, broad-exception-caught
 # pylint: disable=unused-variable
 
+import io
 import os
 import sys
 import time
@@ -143,12 +144,16 @@ def compute(self):
             self.msg = ''
 
             # Parse input dataframe
-            inputs = pd.DataFrame().from_dict(self.input['input-data'])
-            inputs.index = pd.to_datetime(inputs.index)#, unit='ms')
+            inputs = pd.read_json(io.StringIO(self.input['input-data']))
+            inputs.index = pd.to_datetime(inputs.index)
 
             # configuration
             self.parameter = self.input['parameter']
 
+            # add demand profiles
+            if self.parameter['wrapper']['compute_loads']:
+                inputs = make_inputs(self.parameter, inputs, return_json=False)['input-data']
+
             # Setup controller
             if self.init:
                 self.init_functions()
@@ -380,9 +385,8 @@ def compute(self):
                 #uShade = df[['Tint Bottom [-]', 'Tint Middle [-]', 'Tint Top [-]']].iloc[0].values
                 self.output['ctrl-facade'] = [round(float(u),1) for u in uShade]
 
-            df.index = (df.index.astype(np.int64) / 10 ** 6).astype(str)
             df = df.astype(float).fillna(-1)
-            self.output['output-data'] = df.to_dict()
+            self.output['output-data'] = df.to_json()
             self.output['duration']['outputs'] = time.time() - st1
             self.output['duration']['all'] = time.time() - st
 
@@ -399,7 +403,7 @@ def compute(self):
                 self.output[k] = None
         return self.msg
 
-def make_inputs(parameter, df, ext_df=pd.DataFrame()):
+def make_inputs(parameter, df, ext_df=pd.DataFrame(), return_json=True):
     """Utility function to make inputs."""
 
     df = df.copy(deep=True)
@@ -422,6 +426,8 @@ def make_inputs(parameter, df, ext_df=pd.DataFrame()):
         raise NotImplementedError
 
     # Default inputs
+    if not 'wind_speed' in df.columns:
+        df.loc[:, 'wind_speed'] = 0
     df.loc[:, 'generation_pv'] = 0
     df.loc[:, 'load_demand'] = 0
     df.loc[:, 'temp_slab_max'] = 1e3
@@ -436,7 +442,10 @@ def make_inputs(parameter, df, ext_df=pd.DataFrame()):
 
     # Map parameter and make Inputs object
     inputs = {}
-    inputs['input-data'] = df.to_dict()
+    if return_json:
+        inputs['input-data'] = df.to_json()
+    else:
+        inputs['input-data'] = df
     inputs['wf-all'] = None
     inputs['facade-initial'] = parameter['facade']['fstate_initial']
     inputs['temps-initial'] = parameter['zone']['temps_initial']
@@ -477,8 +486,7 @@ def make_inputs(parameter, df, ext_df=pd.DataFrame()):
     print('Log-message:\n', ctrl.do_step(inputs=inputs))
     print('Duration:\n', ctrl.get_output(keys=['duration']))
     print('Optimization:\n', ctrl.get_output(keys=['opt-stats']))
-    df = pd.DataFrame(ctrl.get_output(keys=['output-data'])['output-data'])
-    df.index = pd.to_datetime(pd.to_numeric(df.index), unit='ms')
+    df = pd.read_json(io.StringIO(ctrl.get_output(keys=['output-data'])['output-data']))
 
     try:
         plot_standard1(pd.concat([wf, df], axis=1).ffill().iloc[:-1])

diff --git a/afc/defaultConfig.py b/afc/defaultConfig.py
@@ -312,6 +312,7 @@ def default_parameter(tariff_name='e19-2020', hvac_control=True,
     output_list = default_output_list(parameter) + afc_output_list()
     parameter['wrapper']['output_list'] = output_list
     parameter['wrapper']['tariff_name'] = tariff_name
+    parameter['wrapper']['compute_loads'] = False
 
     return parameter
 

diff --git a/dev/Development-ControllerWrapper.ipynb b/dev/Development-ControllerWrapper.ipynb
@@ -66,9 +66,9 @@
       "CO2 Emissions [kg]\t\t0.0\n",
       "\n",
       "Duration:\n",
-      " {'duration': {'radiance': 30.463333129882812, 'glare': 69.8858585357666, 'varts': 0.13012290000915527, 'optall': 0.5115549564361572, 'outputs': 0.00562286376953125, 'all': 105.02531147003174}}\n",
+      " {'duration': {'radiance': 31.48572826385498, 'glare': 69.95852065086365, 'varts': 0.1322014331817627, 'optall': 0.5194482803344727, 'outputs': 0.001718282699584961, 'all': 106.26495265960693}}\n",
       "Optimization:\n",
-      " {'opt-stats': {'duration': 0.20725703239440918, 'termination': 'optimal', 'objective': 20.28974844}}\n"
+      " {'opt-stats': {'duration': 0.20727014541625977, 'termination': 'optimal', 'objective': 20.28974844}}\n"
      ]
     },
     {
@@ -97,6 +97,7 @@
     "# pylint: disable=too-many-branches, too-many-statements, broad-exception-caught\n",
     "# pylint: disable=unused-variable\n",
     "\n",
+    "import io\n",
     "import os\n",
     "import sys\n",
     "import time\n",
@@ -228,12 +229,16 @@
     "            self.msg = ''\n",
     "\n",
     "            # Parse input dataframe\n",
-    "            inputs = pd.DataFrame().from_dict(self.input['input-data'])\n",
-    "            inputs.index = pd.to_datetime(inputs.index)#, unit='ms')\n",
+    "            inputs = pd.read_json(io.StringIO(self.input['input-data']))\n",
+    "            inputs.index = pd.to_datetime(inputs.index)\n",
     "\n",
     "            # configuration\n",
     "            self.parameter = self.input['parameter']\n",
     "\n",
+    "            # add demand profiles\n",
+    "            if self.parameter['wrapper']['compute_loads']:\n",
+    "                inputs = make_inputs(self.parameter, inputs, return_json=False)['input-data']\n",
+    "\n",
     "            # Setup controller\n",
     "            if self.init:\n",
     "                self.init_functions()\n",
@@ -465,9 +470,8 @@
     "                #uShade = df[['Tint Bottom [-]', 'Tint Middle [-]', 'Tint Top [-]']].iloc[0].values\n",
     "                self.output['ctrl-facade'] = [round(float(u),1) for u in uShade]\n",
     "\n",
-    "            df.index = (df.index.astype(np.int64) / 10 ** 6).astype(str)\n",
     "            df = df.astype(float).fillna(-1)\n",
-    "            self.output['output-data'] = df.to_dict()\n",
+    "            self.output['output-data'] = df.to_json()\n",
     "            self.output['duration']['outputs'] = time.time() - st1\n",
     "            self.output['duration']['all'] = time.time() - st\n",
     "\n",
@@ -484,7 +488,7 @@
     "                self.output[k] = None\n",
     "        return self.msg\n",
     "\n",
-    "def make_inputs(parameter, df, ext_df=pd.DataFrame()):\n",
+    "def make_inputs(parameter, df, ext_df=pd.DataFrame(), return_json=True):\n",
     "    \"\"\"Utility function to make inputs.\"\"\"\n",
     "\n",
     "    df = df.copy(deep=True)\n",
@@ -507,6 +511,8 @@
     "        raise NotImplementedError\n",
     "\n",
     "    # Default inputs\n",
+    "    if not 'wind_speed' in df.columns:\n",
+    "        df.loc[:, 'wind_speed'] = 0\n",
     "    df.loc[:, 'generation_pv'] = 0\n",
     "    df.loc[:, 'load_demand'] = 0\n",
     "    df.loc[:, 'temp_slab_max'] = 1e3\n",
@@ -521,7 +527,10 @@
     "\n",
     "    # Map parameter and make Inputs object\n",
     "    inputs = {}\n",
-    "    inputs['input-data'] = df.to_dict()\n",
+    "    if return_json:\n",
+    "        inputs['input-data'] = df.to_json()\n",
+    "    else:\n",
+    "        inputs['input-data'] = df\n",
     "    inputs['wf-all'] = None\n",
     "    inputs['facade-initial'] = parameter['facade']['fstate_initial']\n",
     "    inputs['temps-initial'] = parameter['zone']['temps_initial']\n",
@@ -562,8 +571,7 @@
     "    print('Log-message:\\n', ctrl.do_step(inputs=inputs))\n",
     "    print('Duration:\\n', ctrl.get_output(keys=['duration']))\n",
     "    print('Optimization:\\n', ctrl.get_output(keys=['opt-stats']))\n",
-    "    df = pd.DataFrame(ctrl.get_output(keys=['output-data'])['output-data'])\n",
-    "    df.index = pd.to_datetime(pd.to_numeric(df.index), unit='ms')\n",
+    "    df = pd.read_json(io.StringIO(ctrl.get_output(keys=['output-data'])['output-data']))\n",
     "\n",
     "    try:\n",
     "        plot_standard1(pd.concat([wf, df], axis=1).ffill().iloc[:-1])\n",