def _input_output_group_relation(block): for p, t in m.TIMEINDEX: for n in group: # Connect input groups - for i, ii in zip(list(n.input_groups)[:-1], list(n.input_groups)[1:]): + for i, ii in zip( + list(n.input_groups)[:-1], list(n.input_groups)[1:] + ): block.input_output_relation.add( (n, i, p, t), ( block.INPUT_GROUP_FLOW[n, i, p, t] == block.INPUT_GROUP_FLOW[n, ii, p, t] ), ) # Connect output groups - for o, oo in zip(list(n.output_groups)[:-1], list(n.output_groups)[1:]): + for o, oo in zip( + list(n.output_groups)[:-1], list(n.output_groups)[1:] + ): block.input_output_relation.add( (n, o, p, t), ( block.OUTPUT_GROUP_FLOW[n, o, p, t] == block.OUTPUT_GROUP_FLOW[n, oo, p, t]

es = EnergySystem(timeindex=idx) # resources b_gas = Bus(label="gas") es.add(b_gas) - es.add(Source(label="gas_station", outputs={b_gas: Flow(fix=[120, 0], nominal_value=1, variable_costs=20)})) + es.add( + Source( + label="gas_station", + outputs={ + b_gas: Flow(fix=[120, 0], nominal_value=1, variable_costs=20) + }, + ) + ) b_hydro = Bus(label="hydro") es.add(b_hydro) - es.add(Source(label="hydro_station", outputs={b_hydro: Flow(fix=[0, 130], nominal_value=1, variable_costs=20)})) + es.add( + Source( + label="hydro_station", + outputs={ + b_hydro: Flow(fix=[0, 130], nominal_value=1, variable_costs=20) + }, + ) + ) b_electricity = Bus(label="electricity") es.add(b_electricity) es.add( Sink(

es.add( MultiInputMultiOutputConverter( label="mimo", inputs={"in": {b_gas: Flow(), b_hydro: Flow()}}, outputs={b_electricity: Flow()}, - conversion_factors={b_gas: 1.2, b_hydro: 1.3} + conversion_factors={b_gas: 1.2, b_hydro: 1.3}, ) ) # create an optimization problem and solve it om = Model(es)

om.solve(solver="cbc") # create result object results = processing.convert_keys_to_strings(processing.results(om)) - assert all(results[("gas", "mimo")]["sequences"]["flow"].values[:-1] == [120.0, 0.0]) - assert all(results[("hydro", "mimo")]["sequences"]["flow"].values[:-1] == [0.0, 130.0]) + assert all( + results[("gas", "mimo")]["sequences"]["flow"].values[:-1] + == [120.0, 0.0] + ) + assert all( + results[("hydro", "mimo")]["sequences"]["flow"].values[:-1] + == [0.0, 130.0] + ) def test_flow_shares(): idx = pd.date_range("1/1/2017", periods=2, freq="H") es = EnergySystem(timeindex=idx) # resources b_gas = Bus(label="gas") es.add(b_gas) - es.add(Source(label="gas_station", outputs={b_gas: Flow(variable_costs=20)})) + es.add( + Source(label="gas_station", outputs={b_gas: Flow(variable_costs=20)}) + ) b_hydro = Bus(label="hydro") es.add(b_hydro) - es.add(Source(label="hydro_station", outputs={b_hydro: Flow(variable_costs=20)})) + es.add( + Source( + label="hydro_station", outputs={b_hydro: Flow(variable_costs=20)} + ) + ) b_electricity = Bus(label="electricity") es.add(b_electricity) es.add( Sink(

MultiInputMultiOutputConverter( label="mimo", inputs={"in": {b_gas: Flow(), b_hydro: Flow()}}, outputs={b_electricity: Flow(), b_heat: Flow()}, conversion_factors={b_gas: 1.2, b_hydro: 1.3}, - input_flow_shares={b_gas: [0.8, 0.3]} + input_flow_shares={b_gas: [0.8, 0.3]}, ) ) # create an optimization problem and solve it om = Model(es)

om.solve(solver="cbc") # create result object results = processing.convert_keys_to_strings(processing.results(om)) - assert all(results[("gas", "mimo")]["sequences"]["flow"].values[:-1] == [100 * 0.8 * 1.2, 100 * 0.3 * 1.2]) - assert all(results[("hydro", "mimo")]["sequences"]["flow"].values[:-1] == [100 * 0.2 * 1.3, 100 * 0.7 * 1.3]) + assert all( + results[("gas", "mimo")]["sequences"]["flow"].values[:-1] + == [100 * 0.8 * 1.2, 100 * 0.3 * 1.2] + ) + assert all( + results[("hydro", "mimo")]["sequences"]["flow"].values[:-1] + == [100 * 0.2 * 1.3, 100 * 0.7 * 1.3] + )