Generic Invest limit

Concurrence for building space

General description

Example that shows how to use “Generic Investment Limit”.

There are two supply chains. The energy systems looks like that:

              bus_a_0          bus_a_1
               |                 |
source_a_0 --->|---> trafo_a --->|--->demand_a
                                 |
                   source_a_1--->|
                                 |

              bus_b_0          bus_b_1
               |                 |
source_b_0 --->|---> trafo_b --->|--->demand_b
                                 |
                   source_b_1--->|
                                 |

Everything is identical - the costs for the sources, the demand, the efficiency of the Converter. And both Converter have an investment at the output. The source ‘*_1’ is in both cases very expensive, so that a investment is probably done in the converter. Now, both investments share a third resource, which is called “space” in this example. (This could be anything, and you could use as many additional resources as you want.) And this resource is limited. In this case, every converter capacity unit, which might be installed, needs 2 space for ‘trafo a’, and 1 space per installed capacity for ‘trafo b’. And the total space is limited to 24. See what happens, have fun ;)

Code

Download source code: example_generic_invest.py

Click to display code

import logging
import os

try:
    import matplotlib.pyplot as plt
except ModuleNotFoundError:
    plt = None

from oemof import solph


def main():
    data = [0, 15, 30, 35, 20, 25, 27, 10, 5, 2, 15, 40, 20, 0, 0]

    # create an energy system
    idx = solph.create_time_index(2020, number=len(data))
    es = solph.EnergySystem(timeindex=idx, infer_last_interval=False)

    # Parameter: costs for the sources
    c_0 = 10
    c_1 = 100

    epc_invest = 500

    # commodity a
    bus_a_0 = solph.Bus(label="bus_a_0")
    bus_a_1 = solph.Bus(label="bus_a_1")
    es.add(bus_a_0, bus_a_1)

    es.add(
        solph.components.Source(
            label="source_a_0",
            outputs={bus_a_0: solph.Flow(variable_costs=c_0)},
        )
    )

    es.add(
        solph.components.Source(
            label="source_a_1",
            outputs={bus_a_1: solph.Flow(variable_costs=c_1)},
        )
    )

    es.add(
        solph.components.Sink(
            label="demand_a",
            inputs={bus_a_1: solph.Flow(fix=data, nominal_value=1)},
        )
    )

    # commodity b
    bus_b_0 = solph.Bus(label="bus_b_0")
    bus_b_1 = solph.Bus(label="bus_b_1")
    es.add(bus_b_0, bus_b_1)
    es.add(
        solph.components.Source(
            label="source_b_0",
            outputs={bus_b_0: solph.Flow(variable_costs=c_0)},
        )
    )

    es.add(
        solph.components.Source(
            label="source_b_1",
            outputs={bus_b_1: solph.Flow(variable_costs=c_1)},
        )
    )

    es.add(
        solph.components.Sink(
            label="demand_b",
            inputs={bus_b_1: solph.Flow(fix=data, nominal_value=1)},
        )
    )

    # Converter a
    es.add(
        solph.components.Converter(
            label="trafo_a",
            inputs={bus_a_0: solph.Flow()},
            outputs={
                bus_a_1: solph.Flow(
                    nominal_value=solph.Investment(
                        ep_costs=epc_invest,
                        custom_attributes={"space": 2},
                    ),
                )
            },
            conversion_factors={bus_a_1: 0.8},
        )
    )

    # Converter b
    es.add(
        solph.components.Converter(
            label="trafo_b",
            inputs={bus_b_0: solph.Flow()},
            outputs={
                bus_b_1: solph.Flow(
                    nominal_value=solph.Investment(
                        ep_costs=epc_invest,
                        custom_attributes={"space": 1},
                    ),
                )
            },
            conversion_factors={bus_a_1: 0.8},
        )
    )

    # create an optimization problem and solve it
    om = solph.Model(es)

    # add constraint for generic investment limit
    om = solph.constraints.additional_investment_flow_limit(
        om, "space", limit=24
    )

    # export lp file
    filename = os.path.join(
        solph.helpers.extend_basic_path("lp_files"), "GenericInvest.lp"
    )
    logging.info("Store lp-file in {0}.".format(filename))
    om.write(filename, io_options={"symbolic_solver_labels": True})

    # solve model
    om.solve(solver="cbc", solve_kwargs={"tee": True})

    # create result object
    results = solph.processing.results(om)

    bus1 = solph.views.node(results, "bus_a_1")["sequences"]
    bus2 = solph.views.node(results, "bus_b_1")["sequences"]

    # plot the time series (sequences) of a specific component/bus
    if plt is not None:
        bus1.plot(kind="line", drawstyle="steps-mid")
        plt.legend()
        plt.show()
        bus2.plot(kind="line", drawstyle="steps-mid")
        plt.legend()
        plt.show()

    space_used = om.invest_limit_space()
    print("Space value: ", space_used)
    print(
        "Investment trafo_a: ",
        solph.views.node(results, "trafo_a")["scalars"][0],
    )
    print(
        "Investment trafo_b: ",
        solph.views.node(results, "trafo_b")["scalars"][0],
    )


if __name__ == "__main__":
    main()

Installation requirements

This example requires oemof.solph (v0.5.x), install by:

pip install oemof.solph[examples]

License

Johannes Röder <johannes.roeder@uni-bremen.de>

MIT license