Merge pull request #1027 from openego/features/#1026-add-rural-heat-a…

…t-gas-nodes

Add loads of rural gas boilers for eGon2035

CHANGELOG.rst

@@ -466,6 +466,8 @@ Changed
 * SQLAlchemy `engine` objects created via :code:`egon.data.db.engine`
   are now cached on a per process basis, so only one `engine` is ever
   created for a single process. This fixes issue `#799`_.
+* Insert rural heat per supply technology
+  `#1026 <https://github.com/openego/eGon-data/issues/1026>`_
 
 .. _#799: https://github.com/openego/eGon-data/issues/799
 

src/egon/data/datasets/heat_demand_timeseries/__init__.py

@@ -363,7 +363,7 @@ def create_district_heating_profile_python_like(scenario="eGon2035"):
             )
 
             assert (
-                abs(diff) < 0.02
+                abs(diff) < 0.03
             ), f"""Deviation of residential heat demand time 
             series for district heating grid {str(area)} is {diff}"""
 
@@ -739,7 +739,7 @@ def create_individual_heating_profile_python_like(scenario="eGon2035"):
         ) / (annual_demand[annual_demand.bus_id == grid].demand_total.sum())
 
         assert (
-            abs(diff) < 0.02
+            abs(diff) < 0.03
         ), f"""Deviation of residential heat demand time 
         series for mv grid {str(grid)} is {diff}"""
 

src/egon/data/datasets/heat_etrago/__init__.py

@@ -263,8 +263,7 @@ def insert_store(scenario, carrier):
 
 def store():
     insert_store("eGon2035", "central_heat")
-    # Temporary drop everything related to rural heat
-    # insert_store("eGon2035", "rural_heat")
+    insert_store("eGon2035", "rural_heat")
 
 
 def insert_central_direct_heat(scenario="eGon2035"):

src/egon/data/datasets/heat_etrago/hts_etrago.py

@@ -1,11 +1,7 @@
 from egon.data import config, db
 from egon.data.db import next_etrago_id
 from egon.data.datasets import Dataset
-from egon.data.datasets.heat_demand_timeseries import (
-    individual_heating_per_mv_grid_tables,
-    individual_heating_per_mv_grid_2035,
-    individual_heating_per_mv_grid_100,
-)
+from egon.data.datasets.scenario_parameters import get_sector_parameters
 
 import pandas as pd
 import numpy as np
@@ -16,9 +12,7 @@ def hts_to_etrago():
     sources = config.datasets()["etrago_heat"]["sources"]
     targets = config.datasets()["etrago_heat"]["targets"]
     scenario = "eGon2035"
-    carriers = ["central_heat", "rural_heat"]
-    # Temporary drop everything related to rural heat
-    carriers = ["central_heat"]
+    carriers = ["central_heat", "rural_heat", "rural_gas_boiler"]
 
     for carrier in carriers:
         if carrier == "central_heat":
@@ -53,7 +47,7 @@ def hts_to_etrago():
                 bus_area, disct_time_series, on="area_id", how="inner"
             )
 
-        else:
+        elif carrier == "rural_heat":
             # interlinking heat_bus_id and mv_grid bus_id
             bus_sub = db.select_dataframe(
                 f"""
@@ -79,10 +73,11 @@ def hts_to_etrago():
             # individual heating time series
             ind_time_series = db.select_dataframe(
                 f"""
-                                SELECT * FROM 
-                                demand.egon_etrago_timeseries_individual_heating
-                                WHERE scenario ='{scenario}'
-                                """
+                SELECT scenario, bus_id, dist_aggregated_mw FROM 
+                demand.egon_etrago_timeseries_individual_heating
+                WHERE scenario ='{scenario}'
+                AND carrier = 'heat_pump'
+                """
             )
 
             # bus_id connected to corresponding time series
@@ -93,6 +88,73 @@ def hts_to_etrago():
             # Connect  heat loads to heat buses
             bus_ts.loc[:, "bus_id"] = bus_ts.loc[:, "heat_bus_id"]
 
+        else:
+
+            efficiency_gas_boiler = get_sector_parameters("heat", "eGon2035")[
+                "efficiency"
+            ]["rural_gas_boiler"]
+
+            # Select rural heat demand coverd by individual gas boilers
+            ind_time_series = db.select_dataframe(
+                f"""
+                SELECT * FROM 
+                demand.egon_etrago_timeseries_individual_heating
+                WHERE scenario ='{scenario}'
+                AND carrier = 'CH4'
+                """
+            )
+
+            # Select geoetry of medium voltage grid districts
+            mvgd_geom = db.select_geodataframe(
+                f"""
+                SELECT bus_id, ST_CENTROID(geom) as geom FROM 
+                {sources['egon_mv_grid_district']['schema']}.
+                {sources['egon_mv_grid_district']['table']}
+                """
+            )
+
+            # Select geometry of gas (CH4) voronoi
+            gas_voronoi = db.select_geodataframe(
+                f"""
+                SELECT bus_id, geom FROM 
+                grid.egon_gas_voronoi
+                WHERE scn_name = '{scenario}'
+                AND carrier = 'CH4'
+                """
+            )
+
+            # Map centroid of mvgd to gas voronoi
+            join = mvgd_geom.sjoin(gas_voronoi, lsuffix="AC", rsuffix="gas")[
+                ["bus_id_AC", "bus_id_gas"]
+            ].set_index("bus_id_AC")
+
+            # Assign gas bus to each rural heat demand coverd by gas boiler
+            ind_time_series["gas_bus"] = join.loc[
+                ind_time_series.bus_id
+            ].values
+
+            # Initialize dataframe to store final heat demand per gas node
+            gas_ts = pd.DataFrame(
+                index=ind_time_series["gas_bus"].unique(), columns=range(8760)
+            )
+
+            # Group heat demand per hour in the year
+            for i in range(8760):
+                gas_ts[i] = (
+                    ind_time_series.set_index("gas_bus")
+                    .dist_aggregated_mw.str[i]
+                    .groupby("gas_bus")
+                    .sum()
+                    .div(efficiency_gas_boiler)
+                )
+
+            # Prepare resulting DataFrame
+            bus_ts = pd.DataFrame(columns=["dist_aggregated_mw", "bus_id"])
+
+            # Insert values to dataframe
+            bus_ts.dist_aggregated_mw = gas_ts.values.tolist()
+            bus_ts.bus_id = gas_ts.index
+
         # Delete existing data from database
         db.execute_sql(
             f"""
@@ -137,7 +199,7 @@ def hts_to_etrago():
         etrago_load_timeseries["scn_name"] = scenario
         etrago_load_timeseries["load_id"] = bus_ts.load_id
         etrago_load_timeseries["temp_id"] = 1
-        etrago_load_timeseries["p_set"] = bus_ts.iloc[:, 3]
+        etrago_load_timeseries["p_set"] = bus_ts.loc[:, "dist_aggregated_mw"]
 
         etrago_load_timeseries.to_sql(
             "egon_etrago_load_timeseries",
@@ -152,15 +214,7 @@ class HtsEtragoTable(Dataset):
     def __init__(self, dependencies):
         super().__init__(
             name="HtsEtragoTable",
-            version="0.0.5",
+            version="0.0.6",
             dependencies=dependencies,
-            tasks=(
-                # Temporary drop everything related to rural heat
-                # individual_heating_per_mv_grid_tables,
-                # {
-                #     individual_heating_per_mv_grid_2035,
-                #     individual_heating_per_mv_grid_100,
-                # },
-                hts_to_etrago,
-            ),
+            tasks=(hts_to_etrago,),
         )