multiyear_data.py

import os
import pvlib
import pandas as pd
from matplotlib import pyplot as plt
import seaborn as sns
sns.set()
plt.ion()

INVERTERS = pvlib.pvsystem.retrieve_sam('CECInverter')
INVERTER_10K = INVERTERS['SMA_America__SB10000TL_US__240V_']
CECMODS = pvlib.pvsystem.retrieve_sam('CECMod')
CECMOD_POLY = CECMODS['Canadian_Solar_Inc__CS6X_300P']
CECMOD_MONO = CECMODS['Canadian_Solar_Inc__CS6X_300M']
LATITUDE, LONGITUDE = 40.5137, -108.5449
NREL_API_KEY = os.getenv('NREL_API_KEY', 'DEMO_KEY')
EMAIL = os.getenv('EMAIL', '[email protected]')

YEARS = [2015, 2016, 2017, 2018, 2019]
EDAILY = []

for year in YEARS:
    header, data = pvlib.iotools.get_psm3(LATITUDE, LONGITUDE, NREL_API_KEY, EMAIL, names=str(year))
    # get solar position
    TIMES = data.index
    sp = pvlib.solarposition.get_solarposition(
            TIMES, LATITUDE, LONGITUDE)
    solar_zenith = sp.apparent_zenith.values
    solar_azimuth = sp.azimuth.values
    dni = data.DNI.values
    ghi = data.GHI.values
    dhi = data.DHI.values
    surface_albedo = data['Surface Albedo'].values
    temp_air = data.Temperature.values
    dni_extra = pvlib.irradiance.get_extra_radiation(TIMES).values

    tracker = pvlib.tracking.singleaxis(solar_zenith, solar_azimuth)
    surface_tilt = tracker['surface_tilt']
    surface_azimuth = tracker['surface_azimuth']
    poa_sky_diffuse = pvlib.irradiance.get_sky_diffuse(
            surface_tilt, surface_azimuth, solar_zenith, solar_azimuth,
            dni, ghi, dhi, dni_extra=dni_extra, model='haydavies')
    aoi = tracker['aoi']
    poa_ground_diffuse = pvlib.irradiance.get_ground_diffuse(
            surface_tilt, ghi, albedo=surface_albedo)
    poa = pvlib.irradiance.poa_components(
            aoi, dni, poa_sky_diffuse, poa_ground_diffuse)
    poa_direct = poa['poa_direct']
    poa_diffuse = poa['poa_diffuse']
    poa_global = poa['poa_global']
    iam = pvlib.iam.ashrae(aoi)
    effective_irradiance = poa_direct*iam + poa_diffuse
    temp_cell = pvlib.temperature.pvsyst_cell(poa_global, temp_air)

    # this is the magic
    cecparams = pvlib.pvsystem.calcparams_cec(
            effective_irradiance, temp_cell,
            CECMOD_MONO.alpha_sc, CECMOD_MONO.a_ref,
            CECMOD_MONO.I_L_ref, CECMOD_MONO.I_o_ref,
            CECMOD_MONO.R_sh_ref, CECMOD_MONO.R_s, CECMOD_MONO.Adjust)
    mpp = pvlib.pvsystem.max_power_point(*cecparams, method='newton')
    mpp = pd.DataFrame(mpp, index=TIMES)
    Edaily = mpp.p_mp.resample('D').sum()
    EDAILY.append(Edaily)

yield_daily = pd.concat(EDAILY) / 300.0 / 24 * 100
yield_daily.plot()
plt.ylabel('Daily DC Capacity [%]')
plt.title('Multiyear data')