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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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Example that shows the parameter `balanced` of `GenericStorage`. |
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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 pandas as pd |
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from matplotlib import pyplot as plt |
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from oemof import solph |
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DATA = [ |
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{ |
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"name": "unbalanced (20% filled)", |
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"initial_storage_level": 0.2, |
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"balanced": False, |
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}, |
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{ |
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"name": "unbalanced (None)", |
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"initial_storage_level": None, |
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"balanced": False, |
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}, |
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{ |
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"name": "balanced (20% filled)", |
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"initial_storage_level": 0.2, |
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"balanced": True, |
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}, |
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{ |
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"name": "balanced (None)", |
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"initial_storage_level": None, |
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"balanced": True, |
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}, |
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] |
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PARAMETER = {"el_price": 10, "ex_price": 5, "nominal_storage_capacity": 7} |
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def storage_example(): |
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timeseries = pd.DataFrame( |
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{"demand_el": [7, 6, 6, 7], "pv_el": [3, 5, 3, 12]} |
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) |
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# create an energy system |
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idx = pd.date_range("1/1/2017", periods=len(timeseries), freq="H") |
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es = solph.EnergySystem(timeindex=idx) |
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for data_set in DATA: |
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name = data_set["name"] |
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# power bus |
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bel = solph.Bus(label="bel_{0}".format(name)) |
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es.add(bel) |
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es.add( |
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solph.components.Source( |
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label="source_el_{0}".format(name), |
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outputs={ |
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bel: solph.Flow(variable_costs=PARAMETER["el_price"]) |
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}, |
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) |
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) |
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es.add( |
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solph.components.Source( |
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label="pv_el_{0}".format(name), |
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outputs={ |
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bel: solph.Flow(fix=timeseries["pv_el"], nominal_value=1) |
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}, |
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) |
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) |
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es.add( |
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solph.components.Sink( |
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label="demand_el_{0}".format(name), |
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inputs={ |
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bel: solph.Flow( |
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fix=timeseries["demand_el"], nominal_value=1 |
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) |
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}, |
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) |
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) |
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es.add( |
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solph.components.Sink( |
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label="excess_{0}".format(name), |
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inputs={bel: solph.Flow()}, |
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) |
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) |
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# Electric Storage |
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es.add( |
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solph.components.GenericStorage( |
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label="storage_elec_{0}".format(name), |
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nominal_storage_capacity=PARAMETER["nominal_storage_capacity"], |
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inputs={bel: solph.Flow()}, |
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outputs={bel: solph.Flow()}, |
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initial_storage_level=data_set["initial_storage_level"], |
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balanced=data_set["balanced"], |
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) |
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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") |
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# create result object |
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results = solph.processing.results(om) |
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components = [x for x in results if x[1] is None] |
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storage_cap = pd.DataFrame() |
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balance = pd.Series(dtype=float) |
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storages = [x[0] for x in components if "storage" in x[0].label] |
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for s in storages: |
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name = s.label |
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storage_cap[name] = results[s, None]["sequences"]["storage_content"] |
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balance[name] = storage_cap.iloc[0][name] - storage_cap.iloc[-1][name] |
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storage_cap.plot( |
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drawstyle="steps-mid", |
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subplots=False, |
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sharey=True, |
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title="Storage content", |
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) |
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storage_cap.plot( |
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drawstyle="steps-mid", |
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subplots=True, |
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sharey=True, |
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title="Storage content", |
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) |
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balance.plot( |
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kind="bar", |
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linewidth=1, |
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edgecolor="#000000", |
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rot=0, |
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ax=plt.subplots()[1], |
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title="Gained energy from storage", |
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) |
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plt.show() |
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if __name__ == "__main__": |
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storage_example() |
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