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# Copyright (C) 2012, 2013 Ben Elliston 

# Copyright (C) 2014 The University of New South Wales 

# 

# This file is free software; you can redistribute it and/or modify it 

# under the terms of the GNU General Public License as published by 

# the Free Software Foundation; either version 3 of the License, or 

# (at your option) any later version. 

 

"""Generation technology costs.""" 

import generators as tech 

 

 

def annuity_factor(t, r): 

    """Return the annuity factor for lifetime t and interest rate r.""" 

    return (1 - (1 / pow(1 + r, t))) / r 

 

 

class NullCosts: 

 

    """All costs are zero. Useful for debugging.""" 

 

    def __init__(self): 

        self.capcost_per_kw_per_yr = {} 

        self.fixed_om_costs = {} 

        self.opcost_per_mwh = {} 

        self.annuityf = 1 

        self.ccs_storage_per_t = 0 

        self.bioenergy_price_per_gj = 0 

        self.coal_price_per_gj = 0 

        self.gas_price_per_gj = 0 

        self.diesel_price_per_litre = 0 

        self.carbon = 0 

 

        for t in [tech.Biofuel, tech.Black_Coal, tech.CCGT, 

                  tech.CCGT_CCS, tech.CentralReceiver, tech.Coal_CCS, 

                  tech.Diesel, tech.DemandResponse, 

                  tech.Geothermal_EGS, tech.Geothermal_HSA, 

                  tech.Hydro, tech.OCGT, tech.ParabolicTrough, 

                  tech.PumpedHydro, tech.PV, tech.Wind, ]: 

            self.capcost_per_kw_per_yr[t] = 0 

            self.opcost_per_mwh[t] = 0 

            self.fixed_om_costs[t] = 0 

 

 

class AETA2012_2030: 

 

    """Australian Energy Technology Assessment (2012) costs for 2030. 

 

    Source: BREE AETA report (2012), bree.gov.au 

    """ 

 

    lifetime = 30 

    escalation = 1.171 

 

    def __init__(self, discount, coal_price, gas_price, ccs_price): 

        """Construct a cost object given discount rate, coal, gas and CCS costs.""" 

        self.discount_rate = discount 

        self.ccs_storage_per_t = ccs_price 

        # bioenergy costs are taken from the CSIRO energy storage report for AEMO 

        self.bioenergy_price_per_gj = 12 

        self.coal_price_per_gj = coal_price 

        self.gas_price_per_gj = gas_price 

        self.diesel_price_per_litre = 1.50 

        self.capcost_per_kw_per_yr = {} 

        self.opcost_per_mwh = {} 

        self.fixed_om_costs = {} 

        self.annuityf = annuity_factor(self.lifetime, discount) 

 

        # Common capital costs 

        table = self.capcost_per_kw_per_yr 

        table[tech.Hydro] = 0 

        table[tech.PumpedHydro] = 0 

        table[tech.Diesel] = 0 

        table[tech.DemandResponse] = 0 

 

        # Variable O&M (VOM) costs 

        table = self.opcost_per_mwh 

        table[tech.Hydro] = 0 

        table[tech.PumpedHydro] = 0 

        table[tech.Diesel] = 0 

        table[tech.Wind] = 12 * self.escalation 

        table[tech.CentralReceiver] = 15 * self.escalation 

        table[tech.ParabolicTrough] = 20 * self.escalation 

        table[tech.PV] = 0 

        table[tech.PV1Axis] = 0 

        table[tech.CCGT] = 4 * self.escalation 

        table[tech.OCGT] = 10 * self.escalation 

        table[tech.CCGT_CCS] = 9 * self.escalation 

        table[tech.Coal_CCS] = 15 * self.escalation 

        table[tech.Black_Coal] = 7 * self.escalation 

        table[tech.Geothermal_HSA] = 0 

        table[tech.Geothermal_EGS] = 0 

        table[tech.Biofuel] = table[tech.OCGT]  # same as OCGT 

 

        # Fixed O&M (FOM) costs 

        table = self.fixed_om_costs 

        table[tech.DemandResponse] = 0 

        table[tech.Diesel] = 0 

        table[tech.Hydro] = 0 

        table[tech.PumpedHydro] = 0 

        table[tech.Wind] = 40 * self.escalation 

        table[tech.CentralReceiver] = 60 * self.escalation 

        table[tech.ParabolicTrough] = 65 * self.escalation 

        table[tech.PV] = 25 * self.escalation 

        table[tech.PV1Axis] = 38 * self.escalation 

        table[tech.CCGT] = 10 * self.escalation 

        table[tech.OCGT] = 4 * self.escalation 

        table[tech.CCGT_CCS] = 17 * self.escalation 

        table[tech.Coal_CCS] = 73.2 * self.escalation 

        table[tech.Black_Coal] = 50.5 * self.escalation 

        table[tech.Geothermal_HSA] = 200 * self.escalation 

        table[tech.Geothermal_EGS] = 170 * self.escalation 

        table[tech.Biofuel] = table[tech.OCGT]  # same as OCGT 

 

 

class AETA2012_2030Low (AETA2012_2030): 

 

    """AETA (2012) costs for 2030, low end of the range.""" 

 

    def __init__(self, discount, coal_price, gas_price, ccs_storage_costs): 

        """Construct a cost object given discount rate, coal, gas and CCS costs. 

 

        >>> obj = AETA2012_2030Low(0.05, 1.00, 9.00, 30) 

        """ 

        AETA2012_2030.__init__(self, discount, coal_price, gas_price, 

                               ccs_storage_costs) 

        af = self.annuityf 

        # capital costs in $/kW 

        table = self.capcost_per_kw_per_yr 

        fom = self.fixed_om_costs 

        table[tech.Wind] = 1701 / af + fom[tech.Wind] 

        table[tech.CentralReceiver] = 4203 / af + fom[tech.CentralReceiver] 

        table[tech.ParabolicTrough] = 4563 / af + fom[tech.ParabolicTrough] 

        table[tech.PV] = 1482 / af + fom[tech.PV] 

        table[tech.PV1Axis] = 2013 / af + fom[tech.PV1Axis] 

        table[tech.CCGT] = 1015 / af + fom[tech.CCGT] 

        table[tech.OCGT] = 694 / af + fom[tech.OCGT] 

        table[tech.CCGT_CCS] = 2095 / af + fom[tech.CCGT_CCS] 

        table[tech.Coal_CCS] = 4453 / af + fom[tech.Coal_CCS] 

        table[tech.Black_Coal] = 2947 / af + fom[tech.Black_Coal] 

        table[tech.Geothermal_HSA] = 6645 / af + fom[tech.Geothermal_HSA] 

        table[tech.Geothermal_EGS] = 10331 / af + fom[tech.Geothermal_EGS] 

        table[tech.Biofuel] = table[tech.OCGT]  # same as OCGT 

 

 

class AETA2012_2030High (AETA2012_2030): 

 

    """AETA (2012) costs for 2030, high end of the range.""" 

 

    def __init__(self, discount, coal_price, gas_price, ccs_storage_costs): 

        """Construct a cost object given discount rate, coal, gas and CCS costs. 

 

        >>> obj = AETA2012_2030High(0.05, 1.00, 9.00, 30) 

        """ 

        AETA2012_2030.__init__(self, discount, coal_price, gas_price, 

                               ccs_storage_costs) 

        af = self.annuityf 

        # capital costs in $/kW 

        table = self.capcost_per_kw_per_yr 

        fom = self.fixed_om_costs 

        table[tech.Wind] = 1917 / af + fom[tech.Wind] 

        table[tech.CentralReceiver] = 5253 / af + fom[tech.CentralReceiver] 

        table[tech.ParabolicTrough] = 5659 / af + fom[tech.ParabolicTrough] 

        table[tech.PV] = 1871 / af + fom[tech.PV] 

        table[tech.PV1Axis] = 2542 / af + fom[tech.PV1Axis] 

        table[tech.CCGT] = 1221 / af + fom[tech.CCGT] 

        table[tech.OCGT] = 809 / af + fom[tech.OCGT] 

        table[tech.CCGT_CCS] = 2405 / af + fom[tech.CCGT_CCS] 

        table[tech.Coal_CCS] = 4727 / af + fom[tech.Coal_CCS] 

        table[tech.Black_Coal] = 3128 / af + fom[tech.Black_Coal] 

        table[tech.Geothermal_HSA] = 7822 / af + fom[tech.Geothermal_HSA] 

        table[tech.Geothermal_EGS] = 11811 / af + fom[tech.Geothermal_EGS] 

        table[tech.Biofuel] = table[tech.OCGT]  # same as OCGT 

 

 

class AETA2012_2030Mid (AETA2012_2030): 

 

    """AETA (2012) costs for 2030, middle of the range.""" 

 

    def __init__(self, discount, coal_price, gas_price, ccs_storage_costs): 

        """Construct a cost object given discount rate, coal, gas and CCS costs. 

 

        >>> obj = AETA2012_2030Mid(0.05, 1.00, 9.00, 30) 

        """ 

        AETA2012_2030.__init__(self, discount, coal_price, gas_price, 

                               ccs_storage_costs) 

 

        low = AETA2012_2030Low(discount, coal_price, gas_price, ccs_storage_costs) 

        high = AETA2012_2030High(discount, coal_price, gas_price, ccs_storage_costs) 

        assert low.opcost_per_mwh == high.opcost_per_mwh 

        assert low.fixed_om_costs == high.fixed_om_costs 

 

        table = self.capcost_per_kw_per_yr 

        lowtable = low.capcost_per_kw_per_yr 

        hightable = high.capcost_per_kw_per_yr 

        for t in lowtable: 

            # The capital cost tables include fixed O&M (f), but 

            # this averaging calculation is safe because: 

            #   (low + f) / 2 + (high + f) / 2 

            # is equivalent to: 

            #   (low + high) / 2 + f 

            table[t] = lowtable[t] / 2 + hightable[t] / 2 

 

 

class AETA2013_2030Low (AETA2012_2030Low): 

    """AETA (2013 update) costs for 2030, low end of the range.""" 

 

    def __init__(self, discount, coal_price, gas_price, ccs_storage_costs): 

        """Construct a cost object given discount rate, coal, gas and CCS costs. 

 

        >>> obj = AETA2013_2030Low(0.05, 1.00, 9.00, 30) 

        """ 

        AETA2012_2030Low.__init__(self, discount, coal_price, gas_price, 

                                  ccs_storage_costs) 

 

        # Override a few O&M costs. 

        fom = self.fixed_om_costs 

        fom[tech.Wind] = 32.5 * self.escalation 

        fom[tech.PV1Axis] = 30 * self.escalation 

        fom[tech.CentralReceiver] = 71.312 * self.escalation 

        fom[tech.ParabolicTrough] = 72.381 * self.escalation 

        vom = self.opcost_per_mwh 

        vom[tech.Wind] = 10 * self.escalation 

        vom[tech.CentralReceiver] = 5.65 * self.escalation 

        vom[tech.ParabolicTrough] = 11.39 * self.escalation 

 

        # Re-calculate annual capital costs for wind and CST. 

        af = self.annuityf 

        table = self.capcost_per_kw_per_yr 

        fom = self.fixed_om_costs 

        table[tech.Wind] = 1701 / af + fom[tech.Wind] 

        table[tech.CentralReceiver] = 4203 / af + fom[tech.CentralReceiver] 

        table[tech.ParabolicTrough] = 4563 / af + fom[tech.ParabolicTrough] 

 

 

class AETA2013_2030High (AETA2012_2030High): 

    """AETA (2013 update) costs for 2030, high end of the range.""" 

 

    def __init__(self, discount, coal_price, gas_price, ccs_storage_costs): 

        """Construct a cost object given discount rate, coal, gas and CCS costs. 

 

        >>> obj = AETA2013_2030High(0.05, 1.00, 9.00, 30) 

        """ 

        AETA2012_2030High.__init__(self, discount, coal_price, gas_price, 

                                   ccs_storage_costs) 

 

        # Override a few O&M costs. 

        fom = self.fixed_om_costs 

        fom[tech.Wind] = 32.5 * self.escalation 

        fom[tech.PV1Axis] = 30 * self.escalation 

        fom[tech.CentralReceiver] = 71.312 * self.escalation 

        fom[tech.ParabolicTrough] = 72.381 * self.escalation 

        vom = self.opcost_per_mwh 

        vom[tech.Wind] = 10 * self.escalation 

        vom[tech.CentralReceiver] = 5.65 * self.escalation 

        vom[tech.ParabolicTrough] = 11.39 * self.escalation 

 

        # Re-calculate annual capital costs for wind and CST. 

        af = self.annuityf 

        table = self.capcost_per_kw_per_yr 

        fom = self.fixed_om_costs 

        table[tech.Wind] = 1917 / af + fom[tech.Wind] 

        table[tech.CentralReceiver] = 5253 / af + fom[tech.CentralReceiver] 

        table[tech.ParabolicTrough] = 5659 / af + fom[tech.ParabolicTrough] 

 

 

class AETA2013_2030Mid (AETA2012_2030): 

 

    """AETA (2013) costs for 2030, middle of the range.""" 

 

    def __init__(self, discount, coal_price, gas_price, ccs_storage_costs): 

        """Construct a cost object given discount rate, coal, gas and CCS costs. 

 

        >>> obj = AETA2013_2030Mid(0.05, 1.00, 9.00, 30) 

        """ 

        AETA2012_2030.__init__(self, discount, coal_price, gas_price, 

                               ccs_storage_costs) 

 

        low = AETA2013_2030Low(discount, coal_price, gas_price, ccs_storage_costs) 

        high = AETA2013_2030High(discount, coal_price, gas_price, ccs_storage_costs) 

        assert low.opcost_per_mwh == high.opcost_per_mwh 

        self.opcost_per_mwh = low.opcost_per_mwh 

        assert low.fixed_om_costs == high.fixed_om_costs 

        self.fixed_om_costs = low.fixed_om_costs 

 

        table = self.capcost_per_kw_per_yr 

        lowtable = low.capcost_per_kw_per_yr 

        hightable = high.capcost_per_kw_per_yr 

        for t in lowtable: 

            # See comment in AETA2012_2030Mid. 

            table[t] = lowtable[t] / 2 + hightable[t] / 2 

 

 

def cost_switch(label): 

    """ 

    Return a class for a given cost scenario. 

 

    >>> cost_switch('AETA2013-in2030-low') # doctest: +ELLIPSIS 

    <class costs.AETA2013_2030Low at 0x...> 

    >>> cost_switch('foo') 

    Traceback (most recent call last): 

      ... 

    ValueError: unknown cost scenario: foo 

    """ 

    try: 

        callback = cost_scenarios[label] 

    except KeyError: 

        print 'valid scenarios:' 

        for k in sorted(cost_scenarios.keys()): 

            print '\t', k 

        raise ValueError('unknown cost scenario: %s' % label) 

    return callback 

 

 

cost_scenarios = {'null': NullCosts, 

                  'AETA2012-in2030-low': AETA2012_2030Low, 

                  'AETA2012-in2030-mid': AETA2012_2030Mid, 

                  'AETA2012-in2030-high': AETA2012_2030High, 

                  'AETA2013-in2030-low': AETA2013_2030Low, 

                  'AETA2013-in2030-mid': AETA2013_2030Mid, 

                  'AETA2013-in2030-high': AETA2013_2030High}