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# -*- coding: utf-8 -*- |
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""" |
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SPDX-FileCopyrightText: Patrik Schönfeldt |
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SPDX-FileCopyrightText: Daniel Niederhöfer |
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SPDX-FileCopyrightText: DLR e.V. |
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SPDX-License-Identifier: MIT |
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""" |
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# %%[imports] |
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import os |
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import matplotlib.pyplot as plt |
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import networkx as nx |
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import numpy as np |
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from oemof.network.graph import create_nx_graph |
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import pandas as pd |
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from oemof import solph |
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# %%[input_data] |
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file_path = os.path.dirname(__file__) |
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filename = os.path.join(file_path, "pv_example_data.csv") |
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input_data = pd.read_csv( |
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filename, index_col="timestep", parse_dates=["timestep"] |
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) |
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input_data.plot(drawstyle="steps") |
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plt.xlim(pd.Timestamp("2020-03-01 00:00"), pd.Timestamp("2020-03-07 00:00")) |
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plt.show() |
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# %%[energy_system] |
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# parse_dates does not set the freq attribute. |
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# However, we want to use it for the EnergySystem. |
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input_data.index.freq = pd.infer_freq(input_data.index) |
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energy_system = solph.EnergySystem( |
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timeindex=input_data.index, |
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infer_last_interval=True, |
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) |
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# %%[dispatch_model] |
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el_bus = solph.Bus(label="electricity") |
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demand = solph.components.Sink( |
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label="demand", |
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inputs={ |
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el_bus: solph.Flow( |
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nominal_capacity=1, |
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fix=input_data["electricity demand (kW)"], |
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) |
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}, |
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) |
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energy_system.add(el_bus, demand) |
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grid = solph.Bus( |
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label="grid", |
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outputs={el_bus: solph.Flow(variable_costs=0.3)}, |
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balanced=False, |
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) |
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energy_system.add(grid) |
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# %%[graph_plotting] |
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plt.figure() |
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graph = create_nx_graph(energy_system) |
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nx.drawing.nx_pydot.write_dot(graph, "home_pv_graph_1.dot") |
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nx.draw(graph, with_labels=True, font_size=8) |
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plt.show() |
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# %%[model_optimisation] |
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model = solph.Model(energy_system) |
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model.solve(solver="cbc", solve_kwargs={"tee": True}) |
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results = solph.processing.results(model) |
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meta_results = solph.processing.meta_results(model) |
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# %%[results] |
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tce = meta_results["objective"] |
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print(f"The total annual costs are {tce:.2f} €.") |
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el_costs = 0.3 * results[(grid, el_bus)]["sequences"]["flow"].sum() |
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print(f"The annual costs for grid electricity are {el_costs:.2f} €.") |
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electricity_flows = solph.views.node(results, "electricity")["sequences"] |
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baseline = np.zeros(len(electricity_flows)) |
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mode = "light" |
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# mode = "dark" |
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if mode == "dark": |
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plt.style.use("dark_background") |
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plt.fill_between( |
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electricity_flows.index, |
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baseline, |
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electricity_flows[(("grid", "electricity"), "flow")], |
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step="pre", |
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label="Grid supply", |
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) |
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plt.step( |
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electricity_flows.index, |
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electricity_flows[(("electricity", "demand"), "flow")], |
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"-", |
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color="darkgrey", |
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label="Electricity demand", |
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) |
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plt.legend() |
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plt.ylabel("Power (kW)") |
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plt.xlim(pd.Timestamp("2020-01-01 00:00"), pd.Timestamp("2020-01-07 00:00")) |
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plt.gcf().autofmt_xdate() |
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plt.savefig(f"home_pv_result-1_{mode}.svg") |
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plt.show() |
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oemof /
oemof-solph
