tests.test_outputlib

Complexity

Total Complexity

0

Size/Duplication

Total Lines	156
Duplicated Lines	0 %

Importance

Changes

0

import os

import pandas as pd

from oemof.solph import EnergySystem
from oemof.solph import Model
from oemof.solph.buses import Bus
from oemof.solph.components import Converter
from oemof.solph.components import Sink
from oemof.solph.components import Source
from oemof.solph.flows import Flow

filename = os.path.join(os.path.dirname(__file__), "input_data.csv")
data = pd.read_csv(filename, sep=",")

bcoal = Bus(label="coal", balanced=False)
bgas = Bus(label="gas", balanced=False)
boil = Bus(label="oil", balanced=False)
blig = Bus(label="lignite", balanced=False)

# electricity and heat
bel = Bus(label="b_el")
bth = Bus(label="b_th")

# an excess and a shortage variable can help to avoid infeasible problems
excess_el = Sink(label="excess_el", inputs={bel: Flow()})
# shortage_el = Source(label='shortage_el',
#                      outputs={bel: Flow(variable_costs=200)})

# sources
wind = Source(
    label="wind",
    outputs={
        bel: Flow(
            fix=data["wind"],
            nominal_capacity=66.3,
        )
    },
)

pv = Source(
    label="pv",
    outputs={
        bel: Flow(
            fix=data["pv"],
            nominal_capacity=65.3,
        )
    },
)

# demands (electricity/heat)
demand_el = Sink(
    label="demand_elec",
    inputs={
        bel: Flow(
            nominal_capacity=85,
            fix=data["demand_el"],
        )
    },
)

demand_th = Sink(
    label="demand_therm",
    inputs={
        bth: Flow(
            nominal_capacity=40,
            fix=data["demand_th"],
        )
    },
)

# power plants
pp_coal = Converter(
    label="pp_coal",
    inputs={bcoal: Flow()},
    outputs={bel: Flow(nominal_capacity=20.2, variable_costs=25)},
    conversion_factors={bel: 0.39},
)

pp_lig = Converter(
    label="pp_lig",
    inputs={blig: Flow()},
    outputs={bel: Flow(nominal_capacity=11.8, variable_costs=19)},
    conversion_factors={bel: 0.41},
)

pp_gas = Converter(
    label="pp_gas",
    inputs={bgas: Flow()},
    outputs={bel: Flow(nominal_capacity=41, variable_costs=40)},
    conversion_factors={bel: 0.50},
)

pp_oil = Converter(
    label="pp_oil",
    inputs={boil: Flow()},
    outputs={bel: Flow(nominal_capacity=5, variable_costs=50)},
    conversion_factors={bel: 0.28},
)

# combined heat and power plant (chp)
pp_chp = Converter(
    label="pp_chp",
    inputs={bgas: Flow()},
    outputs={
        bel: Flow(nominal_capacity=30, variable_costs=42),
        bth: Flow(nominal_capacity=40),
    },
    conversion_factors={bel: 0.3, bth: 0.4},
)

# heatpump with a coefficient of performance (COP) of 3
b_heat_source = Bus(label="b_heat_source")

heat_source = Source(label="heat_source", outputs={b_heat_source: Flow()})

cop = 3
heat_pump = Converter(
    label="heat_pump",
    inputs={bel: Flow(), b_heat_source: Flow()},
    outputs={bth: Flow(nominal_capacity=10)},
    conversion_factors={bel: 1 / 3, b_heat_source: (cop - 1) / cop},
)

datetimeindex = pd.date_range("1/1/2012", periods=24, freq="h")
energysystem = EnergySystem(timeindex=datetimeindex, infer_last_interval=True)
energysystem.add(
    bcoal,
    bgas,
    boil,
    bel,
    bth,
    blig,
    excess_el,
    wind,
    pv,
    demand_el,
    demand_th,
    pp_coal,
    pp_lig,
    pp_oil,
    pp_gas,
    pp_chp,
    b_heat_source,
    heat_source,
    heat_pump,
)

# ################################ optimization ###########################

# create optimization model based on energy_system
optimization_model = Model(energysystem=energysystem)

# solve problem
optimization_model.solve()