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describe biomass

scripts/build_biomass_potentials.py

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