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# -*- coding: utf-8 -*- |
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""" |
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General description |
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------------------- |
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This example illustrates the effect of activity_costs. |
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There are the following components: |
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- demand_heat: heat demand (constant, for the sake of simplicity) |
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- fireplace: wood firing, burns "for free" if somebody is around |
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- boiler: gas firing, consumes (paid) gas |
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Notice that activity_costs is an attribute to NonConvex. |
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This is because it relies on the activity status of a component |
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which is only available for nonconvex flows. |
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Installation requirements |
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------------------------- |
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This example requires oemof.solph (v0.5.x), install by: |
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pip install oemof.solph[examples] |
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License |
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------- |
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`MIT license <https://github.com/oemof/oemof-solph/blob/dev/LICENSE>`_ |
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""" |
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import matplotlib.pyplot as plt |
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import numpy as np |
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import pandas as pd |
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from oemof import solph |
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def main(): |
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########################################################################## |
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# Calculate parameters and initialize the energy system and |
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########################################################################## |
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periods = 24 |
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time = pd.date_range("1/1/2018", periods=periods, freq="H") |
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demand_heat = np.full(periods, 5) |
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demand_heat[:4] = 0 |
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demand_heat[4:18] = 4 |
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activity_costs = np.full(periods, 5) |
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activity_costs[18:] = 0 |
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es = solph.EnergySystem(timeindex=time) |
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b_heat = solph.Bus(label="b_heat") |
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es.add(b_heat) |
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sink_heat = solph.components.Sink( |
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label="demand", |
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inputs={b_heat: solph.Flow(fix=demand_heat, nominal_value=1)}, |
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) |
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fireplace = solph.components.Source( |
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label="fireplace", |
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outputs={ |
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b_heat: solph.Flow( |
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nominal_value=3, |
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variable_costs=0, |
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nonconvex=solph.NonConvex(activity_costs=activity_costs), |
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) |
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}, |
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) |
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boiler = solph.components.Source( |
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label="boiler", |
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outputs={b_heat: solph.Flow(nominal_value=10, variable_costs=1)}, |
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) |
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es.add(sink_heat, fireplace, boiler) |
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########################################################################## |
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# Optimise the energy system |
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########################################################################## |
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# create an optimization problem and solve it |
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om = solph.Model(es) |
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# solve model |
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om.solve(solver="cbc", solve_kwargs={"tee": True}) |
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########################################################################## |
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# Check and plot the results |
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########################################################################## |
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results = solph.processing.results(om) |
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# plot data |
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data = solph.views.node(results, "b_heat")["sequences"] |
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ax = data.plot(kind="line", drawstyle="steps-post", grid=True, rot=0) |
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ax.set_xlabel("Time") |
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ax.set_ylabel("Heat (arb. units)") |
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plt.show() |
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if __name__ == "__main__": |
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main() |
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oemof /
oemof-solph
