65 lines
2.1 KiB
Python
65 lines
2.1 KiB
Python
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import pandas as pd
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idx = pd.IndexSlice
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def build_biomass_potentials():
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#delete empty column C from this sheet first before reading it in
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df = pd.read_excel(snakemake.input.jrc_potentials,
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"Potentials (PJ)",
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index_col=[0,1])
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df.rename(columns={"Unnamed: 18":"Municipal waste"},inplace=True)
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df.drop(columns="Total",inplace=True)
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df.replace("-",0.,inplace=True)
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df_dict = {}
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for i in range(36):
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df_dict[df.iloc[i*16,1]] = df.iloc[1+i*16:(i+1)*16].astype(float)
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df_new = pd.concat(df_dict)
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# solid biomass includes: Primary agricultural residues (MINBIOAGRW1),
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# Forestry energy residue (MINBIOFRSF1),
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# Secondary forestry residues (MINBIOWOOW1),
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# Secondary Forestry residues – sawdust (MINBIOWOO1a)',
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# Forestry residues from landscape care biomass (MINBIOFRSF1a),
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# Municipal waste (MINBIOMUN1)',
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# biogas includes : Manure biomass potential (MINBIOGAS1),
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# Sludge biomass (MINBIOSLU1)
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us_type = pd.Series(index=df_new.columns)
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us_type.iloc[0:7] = "not included"
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us_type.iloc[7:8] = "biogas"
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us_type.iloc[8:9] = "solid biomass"
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us_type.iloc[9:11] = "not included"
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us_type.iloc[11:16] = "solid biomass"
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us_type.iloc[16:17] = "biogas"
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#convert from PJ to MWh
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biomass_potentials = df_new.loc[idx[:,snakemake.config['biomass']['year'],snakemake.config['biomass']['scenario']],:].groupby(us_type,axis=1).sum().groupby(level=0).sum().rename({"UK" : "GB", "BH" : "BA"})/3.6*1e6
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biomass_potentials.to_csv(snakemake.output.biomass_potentials)
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if __name__ == "__main__":
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# Detect running outside of snakemake and mock snakemake for testing
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if 'snakemake' not in globals():
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from vresutils import Dict
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import yaml
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snakemake = Dict()
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snakemake.input = Dict()
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snakemake.input['jrc_potentials'] = "data/biomass/JRC Biomass Potentials.xlsx"
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snakemake.output = Dict()
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snakemake.output['biomass_potentials'] = 'data/biomass_potentials.csv'
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with open('config.yaml') as f:
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snakemake.config = yaml.load(f)
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build_biomass_potentials()
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