Don't remove capital cost for lines and links when setting lv, lc limit (#183)
* solve #175 * adjust wildcards explanation * allow lv and lc limits below 1
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FabianHofmann
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@ -23,6 +23,7 @@ Upcoming Release
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* Corrected setting of exogenous emission price (in config -> cost -> emission price). This was not weighted by the efficiency and effective emission of the generators. Fixed in `#171 <https://github.com/PyPSA/pypsa-eur/pull/171>`_.
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* Don't remove capital costs from lines and links, when imposing a line volume limit (wildcard ``lv``) or a line cost limit (``lc``). Previously, these were removed to move the expansion in direction of the limit.
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PyPSA-Eur 0.2.0 (8th June 2020)
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==================================
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@ -9,8 +9,8 @@ Prepare PyPSA network for solving according to :ref:`opts` and :ref:`ll`, such a
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- adding an annual **limit** of carbon-dioxide emissions,
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- adding an exogenous **price** per tonne emissions of carbon-dioxide (or other kinds),
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- setting an **N-1 security margin** factor for transmission line capacities,
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- specifying a limit on the **cost** of transmission expansion,
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- specifying a limit on the **volume** of transmission expansion, and
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- specifying an expansion limit on the **cost** of transmission expansion,
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- specifying an expansion limit on the **volume** of transmission expansion, and
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- reducing the **temporal** resolution by averaging over multiple hours.
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Relevant Settings
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@ -79,6 +79,7 @@ def add_co2limit(n, Nyears=1., factor=None):
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carrier_attribute="co2_emissions", sense="<=",
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constant=annual_emissions * Nyears)
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def add_emission_prices(n, emission_prices=None, exclude_co2=False):
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if emission_prices is None:
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emission_prices = snakemake.config['costs']['emission_prices']
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@ -90,85 +91,47 @@ def add_emission_prices(n, emission_prices=None, exclude_co2=False):
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su_ep = n.storage_units.carrier.map(ep) / n.storage_units.efficiency_dispatch
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n.storage_units['marginal_cost'] += su_ep
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def set_line_s_max_pu(n):
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# set n-1 security margin to 0.5 for 37 clusters and to 0.7 from 200 clusters
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n_clusters = len(n.buses)
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s_max_pu = np.clip(0.5 + 0.2 * (n_clusters - 37) / (200 - 37), 0.5, 0.7)
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n.lines['s_max_pu'] = s_max_pu
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def set_line_cost_limit(n, lc, Nyears=1.):
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def set_transmission_limit(n, ll_type, factor, Nyears=1):
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links_dc_b = n.links.carrier == 'DC' if not n.links.empty else pd.Series()
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lines_s_nom = n.lines.s_nom.where(
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n.lines.type == '',
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np.sqrt(3) * n.lines.num_parallel *
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n.lines.type.map(n.line_types.i_nom) *
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n.lines.bus0.map(n.buses.v_nom)
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)
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_lines_s_nom = (np.sqrt(3) * n.lines.type.map(n.line_types.i_nom) *
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n.lines.num_parallel * n.lines.bus0.map(n.buses.v_nom))
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lines_s_nom = n.lines.s_nom.where(n.lines.type == '', _lines_s_nom)
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n.lines['capital_cost_lc'] = n.lines['capital_cost']
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n.links['capital_cost_lc'] = n.links['capital_cost']
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total_line_cost = ((lines_s_nom * n.lines['capital_cost_lc']).sum() +
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n.links.loc[links_dc_b].eval('p_nom * capital_cost_lc').sum())
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if lc == 'opt':
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costs = load_costs(Nyears, snakemake.input.tech_costs,
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snakemake.config['costs'], snakemake.config['electricity'])
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update_transmission_costs(n, costs, simple_hvdc_costs=False)
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else:
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# Either line_volume cap or cost
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n.lines['capital_cost'] = 0.
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n.links.loc[links_dc_b, 'capital_cost'] = 0.
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col = 'capital_cost' if ll_type == 'c' else 'length'
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ref = (lines_s_nom @ n.lines[col] +
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n.links[links_dc_b].p_nom @ n.links[links_dc_b][col])
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if lc == 'opt' or float(lc) > 1.0:
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costs = load_costs(Nyears, snakemake.input.tech_costs,
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snakemake.config['costs'],
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snakemake.config['electricity'])
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update_transmission_costs(n, costs, simple_hvdc_costs=False)
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if factor == 'opt' or float(factor) > 1.0:
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n.lines['s_nom_min'] = lines_s_nom
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n.lines['s_nom_extendable'] = True
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n.links.loc[links_dc_b, 'p_nom_min'] = n.links.loc[links_dc_b, 'p_nom']
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n.links.loc[links_dc_b, 'p_nom_extendable'] = True
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if lc != 'opt':
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line_cost = float(lc) * total_line_cost
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n.add('GlobalConstraint', 'lc_limit',
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type='transmission_expansion_cost_limit',
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sense='<=', constant=line_cost, carrier_attribute='AC, DC')
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if factor != 'opt':
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con_type = 'expansion_cost' if ll_type == 'c' else 'volume_expansion'
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rhs = float(factor) * ref
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n.add('GlobalConstraint', f'l{ll_type}_factor',
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type=f'transmission_{con_type}_limit',
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sense='<=', constant=rhs, carrier_attribute='AC, DC')
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return n
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def set_line_volume_limit(n, lv, Nyears=1.):
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links_dc_b = n.links.carrier == 'DC' if not n.links.empty else pd.Series()
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lines_s_nom = n.lines.s_nom.where(
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n.lines.type == '',
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np.sqrt(3) * n.lines.num_parallel *
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n.lines.type.map(n.line_types.i_nom) *
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n.lines.bus0.map(n.buses.v_nom)
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)
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total_line_volume = ((lines_s_nom * n.lines['length']).sum() +
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n.links.loc[links_dc_b].eval('p_nom * length').sum())
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if lv == 'opt':
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costs = load_costs(Nyears, snakemake.input.tech_costs,
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snakemake.config['costs'], snakemake.config['electricity'])
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update_transmission_costs(n, costs, simple_hvdc_costs=True)
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else:
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# Either line_volume cap or cost
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n.lines['capital_cost'] = 0.
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n.links.loc[links_dc_b, 'capital_cost'] = 0.
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if lv == 'opt' or float(lv) > 1.0:
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n.lines['s_nom_min'] = lines_s_nom
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n.lines['s_nom_extendable'] = True
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n.links.loc[links_dc_b, 'p_nom_min'] = n.links.loc[links_dc_b, 'p_nom']
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n.links.loc[links_dc_b, 'p_nom_extendable'] = True
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if lv != 'opt':
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line_volume = float(lv) * total_line_volume
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n.add('GlobalConstraint', 'lv_limit',
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type='transmission_volume_expansion_limit',
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sense='<=', constant=line_volume, carrier_attribute='AC, DC')
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return n
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def average_every_nhours(n, offset):
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logger.info('Resampling the network to {}'.format(offset))
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@ -191,7 +154,7 @@ if __name__ == "__main__":
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if 'snakemake' not in globals():
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from _helpers import mock_snakemake
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snakemake = mock_snakemake('prepare_network', network='elec', simpl='',
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clusters='5', ll='copt', opts='Co2L-24H')
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clusters='40', ll='v0.3', opts='Co2L-24H')
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configure_logging(snakemake)
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opts = snakemake.wildcards.opts.split('-')
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@ -234,9 +197,6 @@ if __name__ == "__main__":
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add_emission_prices(n)
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ll_type, factor = snakemake.wildcards.ll[0], snakemake.wildcards.ll[1:]
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if ll_type == 'v':
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set_line_volume_limit(n, factor, Nyears)
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elif ll_type == 'c':
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set_line_cost_limit(n, factor, Nyears)
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set_transmission_limit(n, ll_type, factor, Nyears)
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n.export_to_netcdf(snakemake.output[0])
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