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solarPOT/Uncertainty/uncertainty_PV.py
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uncertainty_PV.py
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import pandas as pd
import xarray as xr
import numpy as np
import util
import os
import time
import sys
## for more details, check reference in Total_radiation_spielwiese
START = int(sys.argv[1])
N_LINES = int(sys.argv[2])
OUTNAME = sys.argv[3]
## ===== CONSTANTS ===== ##
CHUNKSIZE = 10000
N_DF_UIDs = 9639231
workdir = '/scratch/walch/workspace_uncertainty'
AREA_FP = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/PRED_available_area_unc_filled.csv'
PV_FP = '/scratch/walch/workspace_tilted_irrad/pv_potential_w_efficiency_new.nc'
GT_UNC_FP = '/scratch/walch/workspace_uncertainty/var_Gt_all.nc'
OUTFILE_FP= os.path.join(workdir, OUTNAME)
END = min(START + N_LINES, N_DF_UIDs)
print('Available area file path: %s' %AREA_FP)
print('PV potential file path: %s' %PV_FP)
print('Tilted area uncertainty file path: %s' %GT_UNC_FP)
print('Output file path: %s' %OUTFILE_FP)
## =========================================================================================== ##
## ===== LOAD DATA ===== ##
tt = time.time()
t0 = time.time()
Gt_unc = xr.open_mfdataset( GT_UNC_FP,chunks={'DF_UID': CHUNKSIZE} ).sortby('DF_UID').isel(DF_UID = range(START, END))
PV_pot = xr.open_mfdataset( PV_FP, chunks={'DF_UID': CHUNKSIZE} ).sortby('DF_UID').isel(DF_UID = range(START, END))
av_area = util.read_csv_rows( AVAIL_AREA_FP, START, N_LINES, usecols = ['DF_UID', 'available_area', 'available_area_std'])
area_ds = av_area.set_index('DF_UID').to_xarray()
print('\n')
print(PV_pot)
print('\n')
print(Gt_unc)
print('\n')
print(area_ds)
print('\n')
print('Loaded all data in %.3f seconds' %(time.time()-tt))
## ===== COMPUTE UNCERTAINTY FOR PV POTENTIAL ===== ##
print('\nComputing uncertainty for PV potential ...')
tt = time.time()
# compute variane of A_PV * G_t (total radiation)
new_var = (area_ds.available_area_std**2 * PV_pot.tilted_irradiance**2
+ Gt_unc.var_Gt_dep * area_ds.available_area**2
+ area_ds.available_area_std**2 * Gt_unc.var_Gt_dep)
# compute variance and standard deviation of PV potential
var_PV = PV_pot.module_eff**2 * PV_pot.PF_mean**2 * new_var
std_PV = PV_pot.module_eff * PV_pot.PF_mean * xr.ufuncs.sqrt(new_var)
unc_PV = xr.merge([std_PV.rename('sigma_PV'), var_PV.rename('var_PV')])
print(unc_PV)
print('Finished in %.3f seconds' %(time.time()-tt))
## ===== PREPARE OUTPUT ===== ##
tt = time.time()
print('\nComputing yearly sums ...')
# Compute yearly sums
unc_PV['yearly_std_PV'] = (util.get_yearly_sum(unc_PV, 'sigma_PV')) / 1000
print(unc_PV)
print('Finished in %.3f seconds' %(time.time()-tt))
tt = time.time()
print('\nSaving output ...')
unc_PV.to_netcdf( OUTFILE_FP )
print('Saved output in %s (%.3fs)' %(OUTFILE_FP, time.time()-tt))
print('\nDONE - total execution time: %.3f seconds' %(time.time()-t0))
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