186 lines
4.8 KiB
Python
186 lines
4.8 KiB
Python
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import pandas as pd
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#allow plotting without Xwindows
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import matplotlib
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matplotlib.use('Agg')
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import matplotlib.pyplot as plt
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#consolidate and rename
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def rename_techs(label):
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if label[:8] == "central ":
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label = label[8:]
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if label[:6] == "urban ":
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label = label[6:]
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if "retrofitting" in label:
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label = "building retrofitting"
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if "H2" in label:
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label = "hydrogen storage"
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if "CHP" in label:
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label = "CHP"
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if "water tank" in label:
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label = "water tanks"
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if label=="water tanks":
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label = "hot water storage"
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if "gas" in label and label != "gas boiler":
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label = "natural gas"
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if "solar thermal" in label:
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label = "solar thermal"
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if label == "solar":
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label = "solar PV"
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if label == "heat pump":
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label = "air heat pump"
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if label == "Sabatier":
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label = "methanation"
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if label == "offwind":
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label = "offshore wind"
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if label == "onwind":
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label = "onshore wind"
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if label == "ror":
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label = "hydroelectricity"
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if label == "hydro":
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label = "hydroelectricity"
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if label == "PHS":
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label = "hydroelectricity"
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if label == "co2 Store":
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label = "DAC"
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if "battery" in label:
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label = "battery storage"
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return label
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preferred_order = pd.Index(["transmission lines","hydroelectricity","hydro reservoir","run of river","pumped hydro storage","onshore wind","offshore wind","solar PV","solar thermal","building retrofitting","ground heat pump","air heat pump","resistive heater","CHP","OCGT","gas boiler","gas","natural gas","methanation","hydrogen storage","battery storage","hot water storage"])
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def plot_costs():
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cost_df = pd.read_csv(snakemake.input.costs,index_col=list(range(3)),header=[0,1,2])
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df = cost_df.groupby(cost_df.index.get_level_values(2)).sum()
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#convert to billions
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df = df/1e9
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df = df.groupby(df.index.map(rename_techs)).sum()
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to_drop = df.index[df.max(axis=1) < snakemake.config['plotting']['costs_threshold']]
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print("dropping")
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print(df.loc[to_drop])
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df = df.drop(to_drop)
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print(df.sum())
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new_index = (preferred_order&df.index).append(df.index.difference(preferred_order))
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new_columns = df.sum().sort_values().index
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fig, ax = plt.subplots()
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fig.set_size_inches((12,8))
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df.loc[new_index,new_columns].T.plot(kind="bar",ax=ax,stacked=True,color=[snakemake.config['plotting']['tech_colors'][i] for i in new_index])
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handles,labels = ax.get_legend_handles_labels()
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handles.reverse()
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labels.reverse()
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ax.set_ylim([0,snakemake.config['plotting']['costs_max']])
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ax.set_ylabel("System Cost [EUR billion per year]")
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ax.set_xlabel("")
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ax.grid(axis="y")
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ax.legend(handles,labels,ncol=4,loc="upper left")
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fig.tight_layout()
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fig.savefig(snakemake.output.costs,transparent=True)
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def plot_energy():
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energy_df = pd.read_csv(snakemake.input.energy,index_col=list(range(2)),header=[0,1,2])
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df = energy_df.groupby(energy_df.index.get_level_values(1)).sum()
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#convert MWh to TWh
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df = df/1e6
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df = df.groupby(df.index.map(rename_techs)).sum()
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to_drop = df.index[df.abs().max(axis=1) < snakemake.config['plotting']['energy_threshold']]
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print("dropping")
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print(df.loc[to_drop])
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df = df.drop(to_drop)
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print(df.sum())
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new_index = (preferred_order&df.index).append(df.index.difference(preferred_order))
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new_columns = df.columns.sort_values()
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fig, ax = plt.subplots()
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fig.set_size_inches((12,8))
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df.loc[new_index,new_columns].T.plot(kind="bar",ax=ax,stacked=True,color=[snakemake.config['plotting']['tech_colors'][i] for i in new_index])
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handles,labels = ax.get_legend_handles_labels()
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handles.reverse()
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labels.reverse()
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ax.set_ylim([snakemake.config['plotting']['energy_min'],snakemake.config['plotting']['energy_max']])
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ax.set_ylabel("Energy [TWh/a]")
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ax.set_xlabel("")
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ax.grid(axis="y")
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ax.legend(handles,labels,ncol=4,loc="upper left")
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fig.tight_layout()
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fig.savefig(snakemake.output.energy,transparent=True)
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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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with open('config.yaml') as f:
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snakemake.config = yaml.load(f)
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snakemake.input = Dict()
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snakemake.output = Dict()
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name = "37-lv"
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for item in ["costs","energy"]:
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snakemake.input[item] = snakemake.config['summary_dir'] + '/{name}/csvs/{item}.csv'.format(name=name,item=item)
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snakemake.output[item] = snakemake.config['summary_dir'] + '/{name}/graphs/{item}.pdf'.format(name=name,item=item)
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plot_costs()
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plot_energy()
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