In MW """ c = vresutils.reatlas.solarpanelconf_to_solar_panel_config_object(panel) return c['A'] + c['B'] * 1000 + c['C'] * np.log(1000) solar_layouts = DEgen.eeg_solarlayouts(graph,cutout) panel_cap = panel_capacity(solar_layouts[0]["panel"]) solar_caps = pd.Series(solar_layouts[1].sum(axis=(1,2))*panel_cap, graph.nodes()) solar_caps.describe(),solar_caps.sum() (generation.solar.max()/solar_caps).describe() windon_layouts = DEgen.eeg_windonlayouts_per_class(graph,cutout) windon_capacities = pd.DataFrame(index=graph.nodes()) for turbine_items in windon_layouts: name = turbine_items[0]["onshore"] turbine_cap = np.array(vresutils.reatlas.turbineconf_to_powercurve_object(name)["POW"]).max() print(name,turbine_cap) windon_capacities[name] = turbine_items[1].sum(axis=(1,2))*turbine_cap/1000. windon_caps = windon_capacities.sum(axis=1) windon_caps.describe(),windon_caps.sum() (generation.windon.max()/windon_caps).describe() windoff_layouts = DEgen.eeg_windofflayouts_per_class(graph,cutout)
""" c = vresutils.reatlas.solarpanelconf_to_solar_panel_config_object(panel) return c['A'] + c['B'] * 1000 + c['C'] * np.log(1000) solar_layouts = DEgen.eeg_solarlayouts(graph, cutout) panel_cap = panel_capacity(solar_layouts[0]["panel"]) solar_caps = pd.Series(solar_layouts[1].sum(axis=(1, 2)) * panel_cap, graph.nodes()) solar_caps.describe(), solar_caps.sum() (generation.solar.max() / solar_caps).describe() windon_layouts = DEgen.eeg_windonlayouts_per_class(graph, cutout) windon_capacities = pd.DataFrame(index=graph.nodes()) for turbine_items in windon_layouts: name = turbine_items[0]["onshore"] turbine_cap = np.array( vresutils.reatlas.turbineconf_to_powercurve_object(name)["POW"]).max() print(name, turbine_cap) windon_capacities[name] = turbine_items[1].sum( axis=(1, 2)) * turbine_cap / 1000. windon_caps = windon_capacities.sum(axis=1) windon_caps.describe(), windon_caps.sum() (generation.windon.max() / windon_caps).describe()