예제 #1
0
def optimise_storage_size(filename="storage_invest.csv",
                          solvername='cbc',
                          debug=True,
                          number_timesteps=8760,
                          tee_switch=True):
    logging.info('Initialize the energy system')
    date_time_index = pd.date_range('1/1/' + str(year),
                                    periods=number_timesteps,
                                    freq='H')

    energysystem = solph.EnergySystem(timeindex=date_time_index)

    # Read data file
    full_filename = os.path.join(os.path.dirname(__file__), filename)
    data = pd.read_csv(full_filename, sep=",")
    data_demand = data['demand_el'] / data['demand_el'].sum()

    ##########################################################################
    # Create oemof object
    ##########################################################################
    consumption = 5165 * 1e6
    wind_installed = 1516 * 1e3
    pv_installed = 1491 * 1e3
    grid_share = 0.75

    logging.info('Create oemof objects')
    # create gas bus
    bgas = solph.Bus(label="natural_gas")

    # create electricity bus
    bel = solph.Bus(label="electricity")

    # create excess component for the electricity bus to allow overproduction
    solph.Sink(label='excess_bel', inputs={bel: solph.Flow()})

    # Create commodity object for import electricity resource
    solph.Source(label='gridsource',
                 outputs={
                     bel:
                     solph.Flow(nominal_value=consumption * grid_share *
                                number_timesteps / 8760,
                                summed_max=1)
                 })

    # create fixed source object for wind
    solph.Source(label='wind',
                 outputs={
                     bel:
                     solph.Flow(actual_value=wind_feedin,
                                nominal_value=wind_installed,
                                fixed=True,
                                fixed_costs=20)
                 })

    # create fixed source object for pv
    solph.Source(label='pv',
                 outputs={
                     bel:
                     solph.Flow(actual_value=pv_feedin,
                                nominal_value=pv_installed,
                                fixed=True,
                                fixed_costs=15)
                 })

    # create simple sink object for demand
    solph.Sink(label='demand',
               inputs={
                   bel:
                   solph.Flow(actual_value=data_demand,
                              fixed=True,
                              nominal_value=consumption)
               })

    # Calculate ep_costs from capex to compare with old solph
    capex = 1000
    lifetime = 20
    wacc = 0.05
    epc = capex * (wacc * (1 + wacc)**lifetime) / ((1 + wacc)**lifetime - 1)

    # create storage transformer object for storage
    solph.Storage(
        label='storage',
        inputs={bel: solph.Flow(variable_costs=10e10)},
        outputs={bel: solph.Flow(variable_costs=10e10)},
        capacity_loss=0.00,
        initial_capacity=0,
        nominal_input_capacity_ratio=1,
        nominal_output_capacity_ratio=1,
        inflow_conversion_factor=1,
        outflow_conversion_factor=0.8,
        fixed_costs=35,
        investment=solph.Investment(ep_costs=epc),
    )

    ##########################################################################
    # Optimise the energy system and plot the results
    ##########################################################################

    logging.info('Optimise the energy system')

    om = solph.OperationalModel(energysystem)

    if debug:
        filename = os.path.join(helpers.extend_basic_path('lp_files'),
                                'storage_invest.lp')
        logging.info('Store lp-file in {0}.'.format(filename))
        om.write(filename, io_options={'symbolic_solver_labels': True})

    logging.info('Solve the optimization problem')
    om.solve(solver=solvername, solve_kwargs={'tee': tee_switch})

    return energysystem
예제 #2
0
def optimise_storage_size(filename="storage_investment.csv",
                          solver='cbc',
                          debug=True,
                          number_timesteps=8760,
                          tee_switch=True):
    logging.info('Initialize the energy system')
    date_time_index = pd.date_range('1/1/2012',
                                    periods=number_timesteps,
                                    freq='H')

    energysystem = solph.EnergySystem(timeindex=date_time_index)

    # Read data file
    full_filename = os.path.join(os.path.dirname(__file__), filename)
    data = pd.read_csv(full_filename, sep=",")

    ##########################################################################
    # Create oemof object
    ##########################################################################

    logging.info('Create oemof objects')
    # create natural gas bus
    bgas = solph.Bus(label="natural_gas")

    # create electricity bus
    bel = solph.Bus(label="electricity")

    # create excess component for the electricity bus to allow overproduction
    solph.Sink(label='excess_bel', inputs={bel: solph.Flow()})

    # create source object representing the natural gas commodity (annual limit)
    solph.Source(label='rgas',
                 outputs={
                     bgas:
                     solph.Flow(nominal_value=194397000 * number_timesteps /
                                8760,
                                summed_max=1)
                 })

    # create fixed source object representing wind power plants
    solph.Source(label='wind',
                 outputs={
                     bel:
                     solph.Flow(actual_value=data['wind'],
                                nominal_value=1000000,
                                fixed=True,
                                fixed_costs=20)
                 })

    # create fixed source object representing pv power plants
    solph.Source(label='pv',
                 outputs={
                     bel:
                     solph.Flow(actual_value=data['pv'],
                                nominal_value=582000,
                                fixed=True,
                                fixed_costs=15)
                 })

    # create simple sink object representing the electrical demand
    solph.Sink(label='demand',
               inputs={
                   bel:
                   solph.Flow(actual_value=data['demand_el'],
                              fixed=True,
                              nominal_value=1)
               })

    # create simple transformer object representing a gas power plant
    solph.LinearTransformer(
        label="pp_gas",
        inputs={bgas: solph.Flow()},
        outputs={bel: solph.Flow(nominal_value=10e10, variable_costs=50)},
        conversion_factors={bel: 0.58})

    # If the period is one year the equivalent periodical costs (epc) of an
    # investment are equal to the annuity. Use oemof's economic tools.
    epc = economics.annuity(capex=1000, n=20, wacc=0.05)

    # create storage object representing a battery
    solph.Storage(
        label='storage',
        inputs={bel: solph.Flow(variable_costs=10e10)},
        outputs={bel: solph.Flow(variable_costs=10e10)},
        capacity_loss=0.00,
        initial_capacity=0,
        nominal_input_capacity_ratio=1 / 6,
        nominal_output_capacity_ratio=1 / 6,
        inflow_conversion_factor=1,
        outflow_conversion_factor=0.8,
        fixed_costs=35,
        investment=solph.Investment(ep_costs=epc),
    )

    ##########################################################################
    # Optimise the energy system and plot the results
    ##########################################################################

    logging.info('Optimise the energy system')

    # initialise the operational model
    om = solph.OperationalModel(energysystem)

    # if debug is true an lp-file will be written
    if debug:
        filename = os.path.join(helpers.extend_basic_path('lp_files'),
                                'storage_invest.lp')
        logging.info('Store lp-file in {0}.'.format(filename))
        om.write(filename, io_options={'symbolic_solver_labels': True})

    # if tee_switch is true solver messages will be displayed
    logging.info('Solve the optimization problem')
    om.solve(solver=solver, solve_kwargs={'tee': tee_switch})

    return energysystem