def test_offsettransformer__too_many_input_flows():
"""Too many Input Flows defined."""
with pytest.raises(ValueError,
match=r"OffsetTransformer` must not have more than 1"):
bgas = Bus(label='GasBus')
bcoal = Bus(label='CoalBus')
components.OffsetTransformer(label='ostf_2_in',
inputs={
bgas:
Flow(nominal_value=60,
min=0.5,
max=1.0,
nonconvex=NonConvex()),
bcoal:
Flow(nominal_value=30,
min=0.3,
max=1.0,
nonconvex=NonConvex())
},
coefficients=(20, 0.5))
def test_offsettransformer_too_many_output_flows():
"""Too many Output Flows defined."""
with pytest.raises(ValueError,
match='OffsetTransformer` must not have more than 1'):
bm1 = Bus(label='my_offset_Bus1')
bm2 = Bus(label='my_offset_Bus2')
components.OffsetTransformer(label='ostf_2_out',
inputs={
bm1:
Flow(nominal_value=60,
min=0.5,
max=1.0,
nonconvex=NonConvex())
},
outputs={
bm1: Flow(),
bm2: Flow()
},
coefficients=(20, 0.5))
def diesel_only(mode,
feedin,
initial_batt_cap,
cost,
iterstatus=None,
PV_source=True,
storage_source=True,
logger=False):
if logger == 1:
logger.define_logging()
##################################### Initialize the energy system##################################################
# times = pd.DatetimeIndex(start='04/01/2017', periods=10, freq='H')
times = feedin.index
energysystem = EnergySystem(timeindex=times)
# switch on automatic registration of entities of EnergySystem-object=energysystem
Node.registry = energysystem
# add components
b_el = Bus(label='electricity')
b_dc = Bus(label='electricity_dc')
b_oil = Bus(label='diesel_source')
demand_feedin = feedin['demand_el']
Sink(label='demand',
inputs={
b_el: Flow(actual_value=demand_feedin,
nominal_value=1,
fixed=True)
})
Sink(label='excess', inputs={b_el: Flow()})
Source(label='diesel', outputs={b_oil: Flow()})
generator1 = custom.DieselGenerator(
label='pp_oil_1',
fuel_input={b_oil: Flow(variable_costs=cost['pp_oil_1']['var'])},
electrical_output={
b_el:
Flow(nominal_value=186,
min=0.3,
max=1,
nonconvex=NonConvex(om_costs=cost['pp_oil_1']['o&m']),
fixed_costs=cost['pp_oil_1']['fix'])
},
fuel_curve={
'1': 42,
'0.75': 33,
'0.5': 22,
'0.25': 16
})
generator2 = custom.DieselGenerator(
label='pp_oil_2',
fuel_input={b_oil: Flow(variable_costs=cost['pp_oil_2']['var'])},
electrical_output={
b_el:
Flow(nominal_value=186,
min=0.3,
max=1,
nonconvex=NonConvex(om_costs=cost['pp_oil_2']['o&m']),
fixed_costs=cost['pp_oil_2']['fix'],
variable_costs=0)
},
fuel_curve={
'1': 42,
'0.75': 33,
'0.5': 22,
'0.25': 16
})
generator3 = custom.DieselGenerator(
label='pp_oil_3',
fuel_input={b_oil: Flow(variable_costs=cost['pp_oil_3']['var'])},
electrical_output={
b_el:
Flow(nominal_value=320,
min=0.3,
max=1,
nonconvex=NonConvex(om_costs=cost['pp_oil_3']['o&m']),
fixed_costs=cost['pp_oil_3']['fix'],
variable_costs=0)
},
fuel_curve={
'1': 73,
'0.75': 57,
'0.5': 38,
'0.25': 27
})
# List all generators in a list called gen_set
gen_set = [generator1, generator2, generator3]
sim_params = get_sim_params(cost)
if mode == 'simulation':
nominal_cap_pv = sim_params['pv']['nominal_capacity']
inv_pv = None
nominal_cap_batt = sim_params['storage']['nominal_capacity']
inv_batt = None
elif mode == 'investment':
nominal_cap_pv = None
inv_pv = sim_params['pv']['investment']
nominal_cap_batt = None
inv_batt = sim_params['storage']['investment']
else:
raise (
UserWarning,
'Energysystem cant be build. Check if mode is spelled correctely. '
'It can be either [simulation] or [investment]')
if PV_source == 1:
PV = Source(label='PV',
outputs={
b_dc:
Flow(nominal_value=nominal_cap_pv,
fixed_costs=cost['pv']['fix'],
actual_value=feedin['PV'],
fixed=True,
investment=inv_pv)
})
else:
PV = None
if storage_source == 1:
storage = components.GenericStorage(
label='storage',
inputs={b_dc: Flow()},
outputs={
b_dc:
Flow(variable_costs=cost['storage']['var'],
fixed_costs=cost['storage']['fix'])
},
nominal_capacity=nominal_cap_batt,
capacity_loss=0.00,
initial_capacity=initial_batt_cap,
nominal_input_capacity_ratio=0.546,
nominal_output_capacity_ratio=0.546,
inflow_conversion_factor=0.92,
outflow_conversion_factor=0.92,
capacity_min=0.5,
capacity_max=1,
investment=inv_batt,
initial_iteration=iterstatus)
else:
storage = None
if storage_source == 1 or PV_source == 1:
inverter1 = add_inverter(b_dc, b_el, 'Inv_pv')
################################# optimization ############################
# create Optimization model based on energy_system
logging.info("Create optimization problem")
m = Model(energysystem)
################################# constraints ############################
sr_requirement = 0.2
sr_limit = demand_feedin * sr_requirement
rm_requirement = 0.4
rm_limit = demand_feedin * rm_requirement
constraints.spinning_reserve_constraint(m,
sr_limit,
groups=gen_set,
storage=storage)
# constraints.n1_constraint(m, demand_feedin, groups=gen_set)
constraints.gen_order_constraint(m, groups=gen_set)
constraints.rotating_mass_constraint(m,
rm_limit,
groups=gen_set,
storage=storage)
return [m, gen_set]
bel = Bus(label="bel")
bgas = Bus(label="bgas")
bth = Bus(label="bth")
Source(label="gas", outputs={bgas: Flow(variable_costs=35)})
Transformer(label='boiler',
inputs={bgas: Flow()},
outputs={
bth:
Flow(nominal_value=500,
variable_cost=50,
nonconvex=NonConvex())
},
conversion_factors={bth: 0.9})
Transformer(label='chp',
inputs={bgas: Flow()},
outputs={
bel: Flow(nominal_value=300, min=0.5, nonconvex=NonConvex()),
bth: Flow()
},
conversion_factors={
bth: 0.3,
bel: 0.45
})
Sink(label='demand_th',
bel: Flow(actual_value=timeseries['demand_el'],
fixed=True, nominal_value=100)})
Source(label='pp_wind',
outputs={
bel: Flow(nominal_value=40, fixed=True,
actual_value=timeseries['wind'])})
Source(label='pp_pv',
outputs={
bel: Flow(nominal_value=20, fixed=True,
actual_value=timeseries['pv'])})
Source(label='pp_gas',
outputs={
bel: Flow(nominal_value=50, nonconvex=NonConvex(),
variable_costs=60,
negative_gradient={'ub': 0.05, 'costs': 0},
positive_gradient={'ub': 0.05, 'costs': 0})})
Source(label='pp_bio',
outputs={
bel: Flow(nominal_value=5,
variable_costs=100)})
components.GenericStorage(
label='storage_el',
inputs={
bel: Flow()},
outputs={
bel: Flow()},
def create_energysystem_model(mode, feedin, initial_batt_cap, cost, iterstatus=None, PV_source=True,
storage_source=True):
"""
The function stes up the energy system model and resturns the operational model m, which equals the
MILP formulation
:param cost: mode optimization mode ['simulation','investment' ] as str
feed timeseries holding pv and demand_el values pd.DataFrame
initial_batt_cap initial SOC of the battery takes float values from 0-1
cost cost dict derived from get_cost_dict() dict
iterstatus None (only important for RH) boolean
PV_source include PV source 'True', exclude 'False' boolean
storage_source include BSS source 'True', exclude 'False' boolean
:return: m operational model oemof.solph.model
gen_set list of oemof.solph.custom.EngineGenerator objects integrated in the model
"""
##################################### Initialize the energy system##################################################
# initialize time steps
# times = pd.DatetimeIndex(start='04/01/2017', periods=10, freq='H')
times = feedin.index
# initialize energy system object
energysystem = EnergySystem( timeindex=times )
# switch on automatic registration of entities of EnergySystem-object=energysystem
Node.registry = energysystem
# add components
b_el = Bus( label='electricity' )
b_dc = Bus( label='electricity_dc' )
b_oil = Bus( label='diesel_source' )
demand_feedin = feedin['demand_el']
Sink( label='demand',
inputs={b_el: Flow( actual_value=demand_feedin,
nominal_value=1,
fixed=True )} )
Sink( label='excess',
inputs={b_el: Flow()} )
# add source in case of capacity shortages, to still find a feasible solution to the problem
# Source(label='shortage_el',
# outputs={b_el: Flow(variable_costs=1000)})
Source( label='diesel',
outputs={b_oil: Flow()} )
generator1 = custom.EngineGenerator( label='pp_oil_1',
fuel_input={b_oil: Flow( variable_costs=cost['pp_oil_1']['var'] )},
electrical_output={b_el: Flow( nominal_value=186,
min=0.3,
max=1,
nonconvex=NonConvex(
om_costs=cost['pp_oil_1']['o&m'] ),
fixed_costs=cost['pp_oil_1']['fix']
)},
fuel_curve={'1': 42, '0.75': 33, '0.5': 22, '0.25': 16} )
generator2 = custom.EngineGenerator( label='pp_oil_2',
fuel_input={b_oil: Flow( variable_costs=cost['pp_oil_2']['var'] )},
electrical_output={b_el: Flow( nominal_value=186,
min=0.3,
max=1,
nonconvex=NonConvex(
om_costs=cost['pp_oil_2']['o&m'] ),
fixed_costs=cost['pp_oil_2']['fix'],
variable_costs=0 )},
fuel_curve={'1': 42, '0.75': 33, '0.5': 22, '0.25': 16} )
generator3 = custom.EngineGenerator( label='pp_oil_3',
fuel_input={b_oil: Flow( variable_costs=cost['pp_oil_3']['var'] )},
electrical_output={b_el: Flow( nominal_value=320,
min=0.3,
max=1,
nonconvex=NonConvex(
om_costs=cost['pp_oil_3']['o&m'] ),
fixed_costs=cost['pp_oil_3']['fix'],
variable_costs=0 )},
fuel_curve={'1': 73, '0.75': 57, '0.5': 38, '0.25': 27} )
# List all generators in a list called gen_set
gen_set = [generator1, generator2, generator3]
sim_params = get_sim_params( cost )
if mode == 'simulation':
nominal_cap_pv = sim_params['pv']['nominal_capacity']
inv_pv = None
nominal_cap_batt = sim_params['storage']['nominal_capacity']
inv_batt = None
elif mode == 'investment':
nominal_cap_pv = None
inv_pv = sim_params['pv']['investment']
nominal_cap_batt = None
inv_batt = sim_params['storage']['investment']
else:
raise (UserWarning, 'Energysystem cant be build. Check if mode is spelled correctely. '
'It can be either [simulation] or [investment]')
if PV_source == 1:
PV = Source( label='PV',
outputs={b_dc: Flow( nominal_value=nominal_cap_pv,
fixed_costs=cost['pv']['fix'],
actual_value=feedin['PV'],
fixed=True,
investment=inv_pv )} )
else:
PV = None
if storage_source == 1:
storage = components.GenericStorage( label='storage',
inputs={b_dc: Flow()},
outputs={b_dc: Flow( variable_costs=cost['storage']['var'] )},
fixed_costs=cost['storage']['fix'],
nominal_capacity=nominal_cap_batt,
capacity_loss=0.00,
initial_capacity=initial_batt_cap,
nominal_input_capacity_ratio=0.546,
nominal_output_capacity_ratio=0.546,
inflow_conversion_factor=0.92,
outflow_conversion_factor=0.92,
capacity_min=0.5,
capacity_max=1,
investment=inv_batt,
initial_iteration=iterstatus )
else:
storage = None
if storage_source == 1 or PV_source == 1:
inverter1 = add_inverter( b_dc, b_el, 'Inv_pv' )
################################# optimization ############################
# create Optimization model based on energy_system
logging.info( "Create optimization problem" )
m = Model( energysystem )
################################# constraints ############################
# add constraints to the model
#spinning reserve constraint
sr_requirement = 0.2
sr_limit = demand_feedin * sr_requirement
#rotating mass constraint
rm_requirement = 0.4
rm_limit = demand_feedin * rm_requirement
constraints.spinning_reserve_constraint( m, sr_limit, groups=gen_set, storage=storage )
#(N-1) is turned of for Lifuka case study
# constraints.n1_constraint(m, demand_feedin, groups=gen_set)
#generator order constraint
constraints.gen_order_constraint( m, groups=gen_set )
constraints.rotating_mass_constraint( m, rm_limit, groups=gen_set, storage=storage )
return [m, gen_set]