def run(self):
sim = Simulator(self.location, self.year_choice, Windturbine(5), terrain_factor = self.terrain_factor )
sim.latitude = self.latitude
sim.longitude = self.longitude
if self.store_wt_out:
P_wt,_ = sim.calc_wind(self.windfeatures)
else:
P_wt = 0
if self.store_sp_out:
P_sp,_ = sim.calc_solar(Az=self.solarfeatures[2::3], Inc=self.solarfeatures[1::3],sp_area=self.solarfeatures[0::3], sp_eff=self.sp_eff)
else:
P_sp = 0
if self.store_total_out:
P_tot,_ = sim.calc_total_power(self.solarfeatures, self.windfeatures, self.sp_eff)
else:
P_tot = 0
data = {'Pwt':P_wt,'Psp': P_sp,'Ptot': P_tot}
self.write_data(data, self.filename)
evt = SimDoneEvent(myEVT_SIMDONE, -1, filename=self.filename)
wx.PostEvent(self.parent, evt)
def collectyeardata(year):
all_stats = pd.DataFrame(columns=['Name','Year','Lat','Lon','cost','solar_cost','wind_cost','cable_cost','cable_area','storage_cost','deficit_cost','total_surplus',
'total_storage','storage_st_cost','zp_st_cost','wt_st_cost','Zp1_angle','Zp1_or','Zp1_area','Zp2_angle','Zp2_or','Zp2_area','Zp3_angle',
'Zp3_or','Zp3_area','Zp4_angle','Zp4_or','Zp4_area','ZP_tot_area','Zp_tot_power','Turbine_n','Turbine_h','Terrain_f','Turbine_tot_power','Total_power'])
for i in range(len(loc_array)):
loc_data = Location(loc_array[i])
file_name = 'Data' + os.sep + 'location_' + str(loc_data.stn) + '.xlsx'
excel_file = pd.ExcelFile(file_name)
years = np.array(excel_file.sheet_names)
if str(year) in years :
sim = Simulator(file_name, str(year), turbine, index_col=0, latitude=loc_data.latitude, longitude=loc_data.longitude, terrain_factor=loc_data.terrain)
configuratie = np.array([[10000,0,0,0],[0,0,0,0],[37,0,0,0]])
sol_power,_ = sim.calc_solar(Az=[0,0,0,0] ,Inc=[37,0,0,0] ,sp_area=[10000,0,0,0])
sol_power_total = np.sum(sol_power)
inputs = {'Name': loc_data.name,
'Year': year,
'Lat': loc_data.latitude,
'Lon': loc_data.longitude,
'storage_st_cost': 0,
'zp_st_cost': 0,
'wt_st_cost': 0,
'Zp1_angle': configuratie[2][0],
'Zp1_or': configuratie[1][0],
'Zp1_area': configuratie[0][0],
'Zp2_angle': configuratie[2][1],
'Zp2_or': configuratie[1][1],
'Zp2_area': configuratie[0][1],
'Zp3_angle': configuratie[2][2],
'Zp3_or': configuratie[1][2],
'Zp3_area': configuratie[0][2],
'Zp4_angle': configuratie[2][3],
'Zp4_or': configuratie[1][3],
'Zp4_area': configuratie[0][3],
'ZP_tot_area': 10000,
'Zp_tot_power': sol_power_total,
'Turbine_n': 0,
'Turbine_h': 0,
'Terrain_f': loc_data.terrain,
'Turbine_tot_power': 0,
'Total_power': 0}
all_stats = all_stats.append(inputs, ignore_index=True)
#Uncomment this to store all the best stats from training
print('Done with: ' + loc_array[i] + '. Year: ' + str(year))
all_stats.to_excel('Output_data' + os.sep + 'solardata_'+ str(year) + '_' + '.xlsx')
tr_rating=loc_data.terrain,
sp_efficiency=16)
best_pick = best_array[0]
best_solar = best_pick[:12]
best_wind = best_pick[-2:]
best_pick_power, _ = sim.calc_total_power(best_solar, best_wind, 16)
total_solar_sm = np.sum(best_solar[0::3])
costings = cost_calc.calculate_cost(best_pick_power, total_solar_sm,
TURBINETYPE, int(best_wind[0]))
stats = cost_calc.get_stats(best_pick_power, total_solar_sm,
TURBINETYPE, int(best_wind[0]))
sol_power, _ = sim.calc_solar(Az=best_solar[2::3],
Inc=best_solar[1::3],
sp_area=best_solar[0::3])
win_power, _ = sim.calc_wind(best_wind)
win_power_total = np.sum(win_power)
sol_power_total = np.sum(sol_power)
inputs = {
'Name': loc_data.name,
'Year': years[j],
'Lat': loc_data.latitude,
'Lon': loc_data.longitude,
'storage_st_cost': 400,
'zp_st_cost': 160,
'wt_st_cost': 3210000,
'Zp1_angle': best_solar[1],
'Zp1_or': best_solar[2],
