emission_constraint_invest.main()

Complexity

Conditions

3

Size

Total Lines	143
Code Lines	85

Duplication

Lines	0
Ratio	0 %

Importance

Changes

0

# -*- coding: utf-8 -*-
def main(optimize=True):
    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_capacity=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_capacity=1)},
        )
    )

    # Converter a
    es.add(
        solph.components.Converter(
            label="trafo_a",
            inputs={bus_a_0: solph.Flow()},
            outputs={
                bus_a_1: solph.Flow(
                    nominal_capacity=solph.Investment(
                        ep_costs=epc_invest,
                        custom_attributes={"emission": 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_capacity=solph.Investment(
                        ep_costs=epc_invest,
                        custom_attributes={"emission": 1},
                    ),
                )
            },
            conversion_factors={bus_a_1: 0.8},
        )
    )

    if optimize is False:
        return es

    # 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, "emission", 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()

    emission_used = om.invest_limit_emission()
    print("Emission value: ", emission_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],
    )