Distribute existing power plants to the correct nodes
Previously they were distributed only by country to the first node in the country. Now conventional power plants are assigned to the correct node using the bus map from PyPSA-Eur. Wind and solar are distributed in each country by capacity factor. The code has been refactored and a bug was fixed whereby total capacities of wind and solar in each country were not correct. Now the years in the config.yaml for myopic are integers not strings.
This commit is contained in:
Tom Brown
parent
b57a6c18f8
commit
658f8ad00c
@ -306,6 +306,8 @@ if config["foresight"] == "myopic":
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rule add_existing_baseyear:
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input:
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network=config['results_dir'] + config['run'] + '/prenetworks/{network}_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{co2_budget_name}_{planning_horizons}.nc',
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powerplants=pypsaeur('resources/powerplants.csv'),
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clustermaps=pypsaeur('resources/clustermaps_{network}_s{simpl}_{clusters}.h5'),
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costs=config['costs_dir'] + "costs_{}.csv".format(config['scenario']['planning_horizons'][0]),
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cop_soil_total="resources/cop_soil_total_{network}_s{simpl}_{clusters}.nc",
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cop_air_total="resources/cop_air_total_{network}_s{simpl}_{clusters}.nc"
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@ -22,7 +22,7 @@ scenario:
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# B for biomass supply, I for industry, shipping and aviation
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# solarx or onwindx changes the available installable potential by factor x
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# dist{n} includes distribution grids with investment cost of n times cost in data/costs.csv
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planning_horizons : ['2020', '2030', '2040', '2050'] #timesteps for myopic and perfect
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planning_horizons : [2020, 2030, 2040, 2050] #timesteps for myopic and perfect
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co2_budget_name: ['go']
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# snapshots are originally set in PyPSA-Eur/config.yaml but used again by PyPSA-Eur-Sec
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@ -48,7 +48,7 @@ biomass:
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scenario: "Med"
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existing_capacities:
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grouping_years: ['1980', '1985', '1990', '1995', '2000','2005','2010','2015', '2019']
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grouping_years: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2019]
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threshold_capacity: 10
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sector:
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@ -42,6 +42,60 @@ override_component_attrs["Generator"].loc["lifetime"] = ["float","years",np.nan,
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override_component_attrs["Store"].loc["build_year"] = ["integer","year",np.nan,"build year","Input (optional)"]
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override_component_attrs["Store"].loc["lifetime"] = ["float","years",np.nan,"build year","Input (optional)"]
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def add_existing_renewables(df_agg):
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cc = pd.read_csv('data/Country_codes.csv',
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index_col=0)
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carriers = {"solar" : "solar",
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"onwind" : "onwind",
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"offwind" : "offwind-ac"}
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for tech in ['solar', 'onwind', 'offwind']:
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carrier = carriers[tech]
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df = pd.read_csv('data/existing_infrastructure/{}_capacity_IRENA.csv'.format(tech),
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index_col=0)
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df = df.fillna(0.)
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df.columns = df.columns.astype(int)
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df.rename(index={'Czechia':'Czech Republic',
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'UK':'United Kingdom',
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'Bosnia Herzg':'Bosnia Herzegovina',
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'North Macedonia': 'Macedonia'}, inplace=True)
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df.rename(index=cc["2 letter code (ISO-3166-2)"], inplace=True)
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# calculate yearly differences
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df.insert(loc=0, value=.0, column='1999')
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df = df.diff(axis=1).drop('1999', axis=1)
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df = df.clip(lower=0)
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#distribute capacities among nodes according to capacity factor
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#weighting with nodal_fraction
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elec_buses = n.buses.index[n.buses.carrier == "AC"]
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nodal_fraction = pd.Series(0.,elec_buses)
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for country in n.buses.loc[elec_buses,"country"].unique():
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gens = [c for c in n.generators_t.p_max_pu.columns if c[:2] == country and c[-len(carrier):] == carrier]
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cfs = n.generators_t.p_max_pu[gens].mean()
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cfs_key = cfs/cfs.sum()
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nodal_fraction.loc[n.generators.loc[gens,"bus"]] = cfs_key.values
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nodal_df = df.loc[n.buses.loc[elec_buses,"country"]]
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nodal_df.index = elec_buses
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nodal_df = nodal_df.multiply(nodal_fraction,axis=0)
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for year in nodal_df.columns:
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for node in nodal_df.index:
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name = f"{node}-{tech}-{year}"
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capacity = nodal_df.loc[node,year]
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if capacity > 0.:
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df_agg.at[name,"Fueltype"] = tech
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df_agg.at[name,"Capacity"] = capacity
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df_agg.at[name,"YearCommissioned"] = year
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df_agg.at[name,"cluster_bus"] = node
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def add_power_capacities_installed_before_baseyear(n, grouping_years, costs):
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"""
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@ -59,7 +113,7 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs):
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### add conventional capacities using 'powerplants.csv'
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df_agg = pd.read_csv('../pypsa-eur/resources/powerplants.csv', index_col=0)
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df_agg = pd.read_csv(snakemake.input.powerplants, index_col=0)
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rename_fuel = {'Hard Coal':'coal',
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'Lignite':'lignite',
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@ -83,104 +137,81 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs):
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df_agg.drop(df_agg.index[df_agg.Technology.isin(technology_to_drop)],inplace=True)
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df_agg.Fueltype = df_agg.Fueltype.map(rename_fuel)
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# add existing solar and wind capacities
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# source: https://www.irena.org/Statistics/Download-Data
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cc = pd.read_csv('data/Country_codes.csv', sep=',', index_col=-1)
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name_to_2code = dict(zip(cc['Country'].tolist(),
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cc['2 letter code (ISO-3166-2)'].tolist()))
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for tech in ['solar', 'onwind', 'offwind']:
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df = pd.read_csv('data/existing_infrastructure/{}_capacity_IRENA.csv'.format(tech),
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sep=',', index_col=0)
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#assign clustered bus
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busmap_s = pd.read_hdf(snakemake.input.clustermaps,
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key="/busmap_s")
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busmap = pd.read_hdf(snakemake.input.clustermaps,
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key="/busmap")
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clustermaps = busmap_s.map(busmap)
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clustermaps.index = clustermaps.index.astype(int)
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df.rename(index={'Czechia':'Czech Republic',
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'UK':'United Kingdom',
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'Bosnia Herzg':'Bosnia Herzegovina',
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'North Macedonia': 'Macedonia'}, inplace=True)
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df.rename(index=lambda country : name_to_2code[country], inplace=True)
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# calculate yearly differences
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df.insert(loc=0, value=.0, column='1999')
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df = df.diff(axis=1).drop('1999', axis=1)
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df = df.clip(lower=0)
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df.replace(to_replace=0.0, value=np.nan, inplace=True)
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for year in df.columns:
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for country in df.index:
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if df.notnull().loc[country,year]:
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df_agg = df_agg.append({'Fueltype':tech,
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'Country':country,
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'Capacity':df.loc[country,year],
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'YearCommissioned':int(year),
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'YearDecommissioning':int(float(year)+costs.at[tech, 'lifetime'])},
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ignore_index=True)
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nodes=set([node[0:2] for node in n.buses.index[n.buses.carrier == "AC"]])
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df_agg["cluster_bus"] = df_agg.bus.map(clustermaps)
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#TODO: Check if we want to change YearCommisioned into YearRetrofited
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for i,grouping_year in enumerate(grouping_years):
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if i==0:
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index = df_agg.YearCommissioned < int(grouping_year)
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#include renewables in df_agg
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add_existing_renewables(df_agg)
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df_agg["grouping_year"] = np.take(grouping_years,
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np.digitize(df_agg.YearCommissioned,
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grouping_years,
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right=True))
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df = df_agg.pivot_table(index=["grouping_year",'Fueltype'], columns='cluster_bus',
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values='Capacity', aggfunc='sum')
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print(df)
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carrier = {"OCGT" : "gas",
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"CCGT" : "gas",
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"coal" : "coal",
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"oil" : "oil",
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"lignite" : "lignite",
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"nuclear" : "uranium"}
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for grouping_year, generator in df.index:
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#capacity is the capacity in MW at each node for this
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capacity = df.loc[grouping_year, generator]
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capacity = capacity[~capacity.isna()]
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capacity = capacity[capacity > snakemake.config['existing_capacities']['threshold_capacity']]
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#print(grouping_year,generator,capacity)
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if generator in ['solar', 'onwind', 'offwind']:
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print("adding generators for",grouping_year,generator,capacity)
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if generator =='offwind':
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p_max_pu=n.generators_t.p_max_pu[capacity.index + ' offwind-ac']
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else:
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p_max_pu=n.generators_t.p_max_pu[capacity.index + ' ' + generator]
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n.madd("Generator",
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capacity.index,
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suffix=' ' + generator +"-"+ str(grouping_year),
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bus=capacity.index,
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carrier=generator,
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p_nom=capacity,
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marginal_cost=costs.at[generator,'VOM'],
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capital_cost=costs.at[generator,'fixed'],
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efficiency=costs.at[generator, 'efficiency'],
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p_max_pu=p_max_pu.rename(columns=n.generators.bus),
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build_year=grouping_year,
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lifetime=costs.at[generator,'lifetime'])
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else:
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index = (int(grouping_years[i-1]) < df_agg.YearCommissioned) & (df_agg.YearCommissioned < int(grouping_year))
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print("adding links for",grouping_year,generator,capacity)
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n.madd("Link",
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capacity.index,
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suffix= " " + generator +"-" + str(grouping_year),
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bus0="EU " + carrier[generator],
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bus1=capacity.index,
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bus2="co2 atmosphere",
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carrier=generator,
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marginal_cost=costs.at[generator,'efficiency']*costs.at[generator,'VOM'], #NB: VOM is per MWel
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capital_cost=costs.at[generator,'efficiency']*costs.at[generator,'fixed'], #NB: fixed cost is per MWel
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p_nom=capacity,
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efficiency=costs.at[generator,'efficiency'],
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efficiency2=costs.at[carrier[generator],'CO2 intensity'],
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build_year=grouping_year,
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lifetime=costs.at[generator,'lifetime'])
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df = df_agg[index].pivot_table(index='Country', columns='Fueltype',
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values='Capacity', aggfunc='sum')
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for node in nodes:
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#if a country has more than one node, selects the first one
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bus_selected=[bus for bus in n.buses.index[n.buses.carrier == "AC"] if bus[0:2]==node][0]
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for generator,carrier in [("OCGT","gas"),
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("CCGT", "gas"),
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("coal", "coal"),
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("oil","oil"),
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("nuclear","uranium")]:
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try:
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if node in df.index and not np.isnan(df.loc[node, generator]):
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#use madd so that we can insert the carrier attribute
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n.madd("Link",
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[bus_selected + " " + generator +"-" + grouping_year],
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bus0="EU " + carrier,
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bus1=bus_selected,
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bus2="co2 atmosphere",
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carrier=generator,
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marginal_cost=costs.at[generator,'efficiency']*costs.at[generator,'VOM'], #NB: VOM is per MWel
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capital_cost=costs.at[generator,'efficiency']*costs.at[generator,'fixed'], #NB: fixed cost is per MWel
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p_nom=df.loc[node, generator],
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efficiency=costs.at[generator,'efficiency'],
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efficiency2=costs.at[carrier,'CO2 intensity'],
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build_year=int(grouping_year),
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lifetime=costs.at[generator,'lifetime'])
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except:
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print("No capacity installed around " + grouping_year + " of " + generator + " in node " + node)
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for generator in ['solar', 'onwind', 'offwind']:
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try:
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if not np.isnan(df.loc[node, generator]):
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if generator =='offwind':
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p_max_pu=n.generators_t.p_max_pu[bus_selected + ' offwind-ac']
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else:
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p_max_pu=n.generators_t.p_max_pu[bus_selected + ' ' + generator]
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n.add("Generator",
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bus_selected + ' ' + generator +"-"+ grouping_year,
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bus=bus_selected,
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carrier=generator,
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p_nom=df.loc[node, generator],
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marginal_cost=costs.at[generator,'VOM'],
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capital_cost=costs.at[generator,'fixed'],
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efficiency=costs.at[generator, 'efficiency'],
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p_max_pu=p_max_pu,
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build_year=int(grouping_year),
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lifetime=costs.at[generator,'lifetime'])
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except:
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print("No capacity installed around " + grouping_year + " of " + generator + " in node " + node)
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# delete generators if their lifetime is over and p_nom=0
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n.mremove("Generator", [index for index in n.generators.index.to_list() if grouping_year in index and n.generators.p_nom[index] < snakemake.config['existing_capacities']['threshold_capacity']])
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n.mremove("Link", [index for index in n.links.index.to_list() if grouping_year in index and n.links.p_nom[index] < snakemake.config['existing_capacities']['threshold_capacity']])
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def add_heating_capacities_installed_before_baseyear(n, baseyear, grouping_years, ashp_cop, gshp_cop, time_dep_hp_cop, costs, default_lifetime):
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@ -281,7 +312,7 @@ def add_heating_capacities_installed_before_baseyear(n, baseyear, grouping_years
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else:
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#installation is assumed to be linear for the past 25 years (default lifetime)
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ratio = (int(grouping_year)-int(grouping_years[i-1]))/default_lifetime
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print(grouping_year + ' ratio ' + str(ratio))
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print(str(grouping_year) + ' ratio ' + str(ratio))
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n.madd("Link",
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nodes[name],
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suffix=" {} {} heat pump-{}".format(name,heat_pump_type, grouping_year),
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@ -336,10 +367,10 @@ def add_heating_capacities_installed_before_baseyear(n, baseyear, grouping_years
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lifetime=costs.at[name_type + ' gas boiler','lifetime'])
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# delete links with p_nom=nan corresponding to extra nodes in country
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n.mremove("Link", [index for index in n.links.index.to_list() if grouping_year in index and np.isnan(n.links.p_nom[index])])
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n.mremove("Link", [index for index in n.links.index.to_list() if str(grouping_year) in index and np.isnan(n.links.p_nom[index])])
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# delete links if their lifetime is over and p_nom=0
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n.mremove("Link", [index for index in n.links.index.to_list() if grouping_year in index and n.links.p_nom[index]<snakemake.config['existing_capacities']['threshold_capacity']])
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n.mremove("Link", [index for index in n.links.index.to_list() if str(grouping_year) in index and n.links.p_nom[index]<snakemake.config['existing_capacities']['threshold_capacity']])
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if __name__ == "__main__":
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@ -51,12 +51,12 @@ def add_lifetime_wind_solar(n):
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n.generators.loc[[index for index in n.generators.index.to_list()
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if carrier in index], 'lifetime']=costs.at[carrier_name,'lifetime']
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def add_coal_oil_uranium_buses(n):
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def add_carrier_buses(n, carriers):
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"""
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Add buses to connect coal, nuclear and oil plants
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Add buses to connect e.g. coal, nuclear and oil plants
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"""
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for carrier in ['coal', 'oil', 'uranium']:
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for carrier in carriers:
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n.add("Carrier",
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carrier)
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@ -1663,7 +1663,7 @@ if __name__ == "__main__":
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if snakemake.config["foresight"]=='myopic':
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add_lifetime_wind_solar(n)
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add_coal_oil_uranium_buses(n)
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add_carrier_buses(n,['lignite', 'coal', 'oil', 'uranium'])
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add_co2_tracking(n)
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Block a user