def peak_load_final(self, category):
title = "Peak Load" + self.plot_title_tail
output_path = self.locator.get_timeseries_plots_file(
self.plot_output_path_header + '_peak_load_supply', category)
analysis_fields = [
"DH_hs0_kW",
"DH_ww0_kW",
'SOLAR_ww0_kW',
'SOLAR_hs0_kW',
"DC_cs0_kW",
'DC_cdata0_kW',
'DC_cre0_kW',
'GRID0_kW',
'PV0_kW',
'NG_hs0_kW',
'COAL_hs0_kW',
'OIL_hs0_kW',
'WOOD_hs0_kW',
'NG_ww0_kW',
'COAL_ww0_kW',
'OIL_ww0_kW',
'WOOD_ww0_kW',
]
data = self.data_processed['yearly_loads'].copy()
analysis_fields = self.erase_zeros(data, analysis_fields)
if len(self.buildings) == 1:
data = data.set_index("Name").ix[self.buildings[0]]
plot = peak_load_building(data, analysis_fields, title,
output_path)
else:
plot = peak_load_district(data, analysis_fields, title,
output_path)
return plot
def peak_load(self, category):
title = "Peak Load" + self.plot_title_tail
output_path = self.locator.get_timeseries_plots_file(
self.plot_output_path_header + '_peak_load', category)
analysis_fields = [
"E_sys0_kW", "Qhs_sys0_kW", "Qww_sys0_kW", "Qcs_sys0_kW",
'Qcdata_sys0_kW', 'Qcre_sys0_kW'
]
data = self.data_processed['yearly_loads'].copy()
if len(self.buildings) == 1:
data = data.set_index("Name").ix[self.buildings[0]]
plot = peak_load_building(data, analysis_fields, title,
output_path)
else:
plot = peak_load_district(data, analysis_fields, title,
output_path)
return plot