def setUpClass(cls):
cls.period = 24
cls.es = EnergySystem(timeindex=pandas.date_range(
'2016-01-01', periods=cls.period, freq='H'))
# BUSSES
b_el1 = Bus(label="b_el1")
b_el2 = Bus(label="b_el2")
b_diesel = Bus(label='b_diesel', balanced=False)
cls.es.add(b_el1, b_el2, b_diesel)
# TEST DIESEL:
dg = Transformer(
label='diesel',
inputs={b_diesel: Flow(variable_costs=2)},
outputs={
b_el1: Flow(variable_costs=1,
investment=Investment(ep_costs=0.5))
},
conversion_factors={b_el1: 2},
)
batt = GenericStorage(
label='storage',
inputs={b_el1: Flow(variable_costs=3)},
outputs={b_el2: Flow(variable_costs=2.5)},
capacity_loss=0.00,
initial_capacity=0,
invest_relation_input_capacity=1 / 6,
invest_relation_output_capacity=1 / 6,
inflow_conversion_factor=1,
outflow_conversion_factor=0.8,
fixed_costs=35,
investment=Investment(ep_costs=0.4),
)
cls.demand_values = [100] * 8760
cls.demand_values[0] = 0.0
demand = Sink(label="demand_el",
inputs={
b_el2:
Flow(nominal_value=1,
actual_value=cls.demand_values,
fixed=True)
})
cls.es.add(dg, batt, demand)
cls.om = Model(cls.es)
cls.om.receive_duals()
cls.om.solve()
cls.mod = Model(cls.es)
cls.mod.solve()
def add_storages(table_collection, nodes):
storages = table_collection["storages"]
storages.columns = storages.columns.swaplevel()
for region in storages["phes"].columns:
storage_label = Label("storage", "electricity", "phes", region)
bus_label = Label("bus", "electricity", "all", region)
params = storages["phes"][region]
nodes[storage_label] = GenericStorage(
label=storage_label,
inputs={nodes[bus_label]: Flow(nominal_value=params.pump)},
outputs={nodes[bus_label]: Flow(nominal_value=params.turbine)},
nominal_storage_capacity=params.energy,
loss_rate=0,
initial_storage_level=None,
inflow_conversion_factor=params.pump_eff,
outflow_conversion_factor=params.turbine_eff,
)
actual_value=data['demand_el'],
fixed=True)
})
# power plants
pp_coal = Transformer(
label='pp_coal',
inputs={bus_coal: Flow()},
outputs={bus_el: Flow(nominal_value=40, emission_factor=0.335)},
conversion_factors={bus_el: 0.39})
storage_el = GenericStorage(label='storage_el',
nominal_storage_capacity=1000,
inputs={bus_el: Flow(nominal_value=200)},
outputs={bus_el: Flow(nominal_value=200)},
loss_rate=0.01,
initial_storage_level=0,
max_storage_level=0.9,
inflow_conversion_factor=0.9,
outflow_conversion_factor=0.9)
# an excess and a shortage variable can help to avoid infeasible problems
excess_el = Sink(label='excess_el', inputs={bus_el: Flow()})
shortage_el = Source(label='shortage_el',
outputs={bus_el: Flow(variable_costs=100000)})
# ## Add all to the energysystem
energysystem.add(bus_coal, bus_gas, bus_el, source_gas, source_coal, wind, pv,
demand_el, pp_coal, storage_el, excess_el, shortage_el)
t_start_warm=3,
t_start_hot=1,
cold_start_costs=5,
warm_start_costs=4,
hot_start_costs=1,
minimum_downtime=1,
ramp_limit_up=3,
ramp_limit_down=4))
},
heat_output={bth: Flow(Q_CW_min=[30 for p in range(0, total_time_steps)])},
Beta=[0.19 for p in range(0, total_time_steps)],
back_pressure=False)
stor = GenericStorage(label='Storage0',
nominal_storage_capacity=100,
inputs={bel: Flow()},
outputs={bel: Flow()},
initial_storage_level=0,
balanced=False)
print(f'Time for es creation: {time()-start}')
start = time()
om = MultiPeriodModel(es, interval_length=48, period=24)
print(f'Time for model creation: {time()-start:.6f}')
# create an optimization problem and solve it
start = time()
om.solve(solver='cplex', solve_kwargs={'tee': True})
print(f'Time for solving: {time()-start:.6f}')
if plt is not None:
def plot_results(results):
# plot electrical bus
excess = Sink(label='excess', inputs={bus_heat: Flow()})
heat_demand = Sink(
label='heat_demand',
inputs={bus_heat: Flow(nominal_value=1, fix=demand_timeseries)})
thermal_storage = GenericStorage(
label='thermal_storage',
inputs={bus_heat: Flow(nominal_value=maximum_heat_flow_charging)},
outputs={
bus_heat:
Flow(nominal_value=maximum_heat_flow_discharging,
variable_costs=0.0001)
},
nominal_storage_capacity=nominal_storage_capacity,
min_storage_level=input_data['min_storage_level'],
max_storage_level=input_data['max_storage_level'],
loss_rate=loss_rate,
fixed_losses_relative=fixed_losses_relative,
fixed_losses_absolute=fixed_losses_absolute,
inflow_conversion_factor=1.0,
outflow_conversion_factor=1.0,
)
energysystem.add(bus_heat, heat_source, shortage, excess, heat_demand,
thermal_storage)
# Create and solve the optimization model
optimization_model = Model(energysystem)
optimization_model.solve(solver=solver,
heat_demand = Sink(label='heat_demand',
inputs={
bus_heat:
Flow(nominal_value=1,
actual_value=demand_timeseries,
fixed=True)
})
thermal_storage = GenericStorage(
label='thermal_storage',
inputs={
bus_heat:
Flow(nominal_value=maximum_heat_flow_charging, variable_costs=0.0001)
},
outputs={bus_heat: Flow(nominal_value=maximum_heat_flow_discharging)},
min_storage_level=min_storage_level,
max_storage_level=max_storage_level,
loss_rate=loss_rate,
fixed_losses_relative=fixed_losses_relative,
fixed_losses_absolute=fixed_losses_absolute,
inflow_conversion_factor=1.,
outflow_conversion_factor=1.,
investment=Investment(ep_costs=400, minimum=1))
energysystem.add(bus_heat, heat_source, shortage, excess, heat_demand,
thermal_storage)
# create and solve the optimization model
optimization_model = Model(energysystem)
optimization_model.write('storage_model.lp',
io_options={'symbolic_solver_labels': True})
inputs={
thbus:
Flow(nominal_value=1,
actual_value=data['demand_th'],
fixed=True)
})
excess_el = Sink(label='excess_el',
inputs={elbus: Flow(variable_costs=-0.005)})
shortage_el = Source(label='shortage_el',
outputs={elbus: Flow(variable_costs=1e10)})
el_storage = GenericStorage(label='el_storage',
inputs={elbus: Flow(variable_costs=0.0001)},
outputs={elbus: Flow()},
loss_rate=0.00,
initial_storage_level=0.5,
invest_relation_input_capacity=1 / 6,
invest_relation_output_capacity=1 / 6,
inflow_conversion_factor=0.9,
outflow_conversion_factor=0.9,
investment=Investment(ep_costs=epc_storage))
cop = 3
es.add(
Transformer(label='heat_pump',
inputs={elbus: Flow()},
outputs={thbus: Flow(nominal_value=10)},
conversion_factors={elbus: 1 / cop}))
th_storage = GenericStorage(label='th_storage',
nominal_storage_capacity=1000,
inputs={thbus: Flow(nominal_value=20)},
bus_simple_thermal_storage = Bus(label='bus_simple_thermal_storage',
balanced=False)
energysystem.add(bus_simple_thermal_storage)
storage_list.append(
GenericStorage(
label='simple_thermal_storage',
inputs={
bus_simple_thermal_storage:
Flow(nominal_value=input_data['maximum_heat_flow_charging'],
variable_costs=0.0001)
},
outputs={
bus_simple_thermal_storage:
Flow(nominal_value=input_data['maximum_heat_flow_discharging'],
variable_costs=0.0001)
},
nominal_storage_capacity=nominal_storage_capacity,
min_storage_level=input_data['min_storage_level'],
max_storage_level=input_data['max_storage_level'],
initial_storage_level=27 / nominal_storage_capacity,
loss_rate=0.001,
inflow_conversion_factor=1.,
outflow_conversion_factor=1.,
balanced=False))
for i, nominal_storage_capacity in enumerate([30, 65, 90]):
bus_i = Bus(label=f'bus_{i}', balanced=False)
energysystem.add(bus_i)
shortage = Source(label='shortage',
outputs={bus_heat: Flow(variable_costs=1e6)})
excess = Sink(label='excess', inputs={bus_heat: Flow()})
heat_demand = Sink(
label='heat_demand',
inputs={bus_heat: Flow(nominal_value=1, fix=demand_timeseries)})
thermal_storage = GenericStorage(
label='thermal_storage',
inputs={bus_heat: Flow(investment=Investment(ep_costs=50))},
outputs={bus_heat: Flow(investment=Investment(), variable_costs=0.0001)},
min_storage_level=input_data['min_storage_level'],
max_storage_level=input_data['max_storage_level'],
loss_rate=loss_rate,
fixed_losses_relative=fixed_losses_relative,
fixed_losses_absolute=fixed_losses_absolute,
inflow_conversion_factor=1.,
outflow_conversion_factor=1.,
invest_relation_input_output=1,
investment=Investment(ep_costs=400, minimum=1))
energysystem.add(bus_heat, heat_source, shortage, excess, heat_demand,
thermal_storage)
# Create and solve the optimization model
optimization_model = Model(energysystem)
optimization_model.solve(solver=solver,
solve_kwargs={
'tee': False,
epc_pv = economics.annuity(capex=1000, n=20, wacc=0.05)
epc_storage = economics.annuity(capex=1000, n=5, wacc=0.05)
pv = Source(label='pv', outputs={elbus: Flow(actual_value=data['pv'], nominal_value=None,
fixed=True, investment=Investment(ep_costs=epc_pv))})
demand_el = Sink(label='demand_el', inputs={elbus: Flow(nominal_value=1, actual_value=data['demand_el'], fixed=True)})
# excess_el = Sink(label='excess_el', inputs={elbus: Flow(variable_costs=0)})
# shortage_el = Source(label='shortage_el', outputs={elbus: Flow(variable_costs=1e30)})
el_storage = GenericStorage(label='el_storage',
inputs={elbus: Flow(variable_costs=0.0001)},
outputs={elbus: Flow()},
loss_rate=0.00,
initial_storage_level=0.6, balanced=True,
invest_relation_input_capacity=1 / 6,
invest_relation_output_capacity=1 / 6,
inflow_conversion_factor=0.9,
outflow_conversion_factor=0.9,
investment=Investment(ep_costs=epc_storage))
grid = GenericStorage(label='grid',
inputs={elbus: Flow(variable_costs=-0.005)},
outputs={elbus: Flow(variable_costs=1.5)},
loss_rate=0.00, nominal_storage_capacity=10000000,
initial_storage_level=0.5, balanced=True,
invest_relation_input_capacity=1,
invest_relation_output_capacity=1,
inflow_conversion_factor=1,
outflow_conversion_factor=1)
actual_value=data['demand_el'],
fixed=True)
})
# power plants
pp_coal = Transformer(
label='pp_coal',
inputs={bus_coal: Flow()},
outputs={bus_el: Flow(nominal_value=40, emission_factor=0.335)},
conversion_factors={bus_el: 0.39})
storage_el = GenericStorage(label='storage_el',
invest=Investment(ep_cost=412),
inputs={bus_el: Flow(nominal_value=200)},
outputs={bus_el: Flow(nominal_value=200)},
loss_rate=0.01,
initial_storage_level=0,
max_storage_level=0.9,
inflow_conversion_factor=0.9,
outflow_conversion_factor=0.9)
# an excess and a shortage variable can help to avoid infeasible problems
excess_el = Sink(label='excess_el', inputs={bus_el: Flow()})
shortage_el = Source(label='shortage_el',
outputs={bus_el: Flow(variable_costs=100000)})
# ## Add all to the energysystem
energysystem.add(bus_coal, bus_gas, bus_el, source_gas, source_coal, wind, pv,
demand_el, pp_coal, storage_el, excess_el, shortage_el)