def get_wind_energy_output(self):
ssc = pssc.PySSC()
f = open(self.sam_export_json)
self.dic = json.load(f)
self.dic['wind_resource_filename'] = self.fp_srw
wp_dat = pssc.dict_to_ssc_table(self.dic, "windpower")
grid_dat = pssc.dict_to_ssc_table(self.dic, "grid")
f.close()
wp = Windpower.wrap(wp_dat)
grid = Grid.from_existing(wp)
grid.assign(Grid.wrap(grid_dat).export())
wp.execute()
grid.execute()
self.json_dict = wp.Outputs.export()
# print(self.json_dict.keys())
# print (self.json_dict['gen'])
self.df_output = pd.DataFrame()
self.df_output[self.year] = self.json_dict['gen']
for col in self.df_output.columns:
self.df_output[col] = preprocessing.minmax_scale(
self.df_output[col].values.reshape(1, -1),
feature_range=(0, 1),
axis=1,
copy=True).T
if self.df_all is None:
self.df_all = self.df_output.copy()
else:
self.df_all = pd.concat([self.df_all, self.df_output], axis=1)
def get_solar_energy_output(self):
ssc = pssc.PySSC()
f = open(self.sam_export_json)
self.dic = json.load(f)
self.dic['solar_resource_file'] = self.fp_srw
### uncomment if you want to change any model input parameters
# self.dic['system_capacity'] = 20000
# self.dic['module_type'] = 0
# self.dic['dc_ac_ratio'] = 1.3
# self.dic['array_type'] = 2
# self.dic['tilt'] = 35
# self.dic['azimuth'] = 180
# self.dic['gcr'] = 0.40
# self.dic['losses'] = 14
# self.dic['en_snowloss'] = 0
# self.dic['inv_eff'] = 95
pv_dat = pssc.dict_to_ssc_table(self.dic, "pvwattsv7")
grid_dat = pssc.dict_to_ssc_table(self.dic, "grid")
f.close()
pv = PVWatts.wrap(pv_dat)
grid = Grid.from_existing(pv)
grid.assign(Grid.wrap(grid_dat).export())
pv.execute()
grid.execute()
self.json_dict = pv.Outputs.export()
# print(self.json_dict.keys())
self.df_output = pd.DataFrame()
self.df_output[self.year] = self.json_dict['gen']
for col in self.df_output.columns:
self.df_output[col] = preprocessing.minmax_scale(
self.df_output[col].values.reshape(1, -1),
feature_range=(0, 1),
axis=1,
copy=True).T
if self.df_all is None:
self.df_all = self.df_output.copy()
else:
self.df_all = pd.concat([self.df_all, self.df_output], axis=1)
Most recently tested against PySAM 2.2.3
@author: frohro
"""
import json
import PySAM.GenericSystem as GenericSystem
import PySAM.Grid as Grid
import PySAM.Singleowner as Singleowner
import PySAM.PySSC as pssc
ssc = pssc.PySSC()
with open("Examples/100mW_Generic.json") as f:
dic = json.load(f)
gs_dat = pssc.dict_to_ssc_table(dic, "generic_system")
grid_dat = pssc.dict_to_ssc_table(dic, "grid")
so_dat = pssc.dict_to_ssc_table(dic, "singleowner")
gs = GenericSystem.wrap(gs_dat)
grid = Grid.from_existing(gs)
grid.assign(Grid.wrap(grid_dat).export())
# to create GenericSystem and Singleowner combined simulation, sharing the same data
so = Singleowner.from_existing(gs)
so.assign(Singleowner.wrap(so_dat).export())
gs.execute()
grid.execute()
so.execute()
print('Made it past execute.')
print(gs.Outputs.export()) # as dictionary