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merge conflicts: apply stash
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Tobin Ford committed Dec 17, 2024
1 parent bd6c8c9 commit e5c04a3
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256 changes: 47 additions & 209 deletions pvdeg/degradation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -863,70 +863,33 @@ def _gJtoMJ(gJ):
return MJ


# new version of degradation
def degradation(
spectra_df: pd.DataFrame,
conditions_df: pd.DataFrame = None,
temp_module: pd.Series = None,
rh_module: pd.Series = None,
spectra: pd.Series,
rh_module: pd.Series,
temp_module: pd.Series,
wavelengths: Union[int, np.ndarray[float]],
Ea: float = 40.0,
n: float = 1.0,
p: float = 0.5,
C2: float = 0.07,
C: float = 1.0,
)-> float:
) -> float:
"""
Compute degredation as double integral of Arrhenius (Activation
Energy, RH, Temperature) and spectral (wavelength, irradiance)
functions over wavelength and time.
.. math::
D = C \\int_{0}^{t} RH(t)^n \\cdot e^{\\frac{-E_a}{RT(t)}} \\int_{\\lambda} [e^{-C_2 \\lambda} \\cdot G(\\lambda, t)]^p d\\lambda dt
Parameters
----------
spectra_df : pd.DataFrame
front or rear irradiance data in dataframe format
- `data`: Spectral irradiance values for each wavelength [W/m^2 nm].
- `index`: pd.DateTimeIndex
- `columns`: Wavelengths as floats (e.g., 280, 300, etc.).
Example::
timestamp 280 300 320 340 360 380 400
2021-03-09 10:00:00 0.6892 0.4022 0.6726 0.0268 0.3398 0.9432 0.7411
2021-03-09 11:00:00 0.1558 0.5464 0.6896 0.7828 0.5050 0.9336 0.4652
2021-03-09 12:00:00 0.2278 0.9057 0.2639 0.0572 0.9906 0.9370 0.1800
2021-03-09 13:00:00 0.3742 0.0358 0.4052 0.9578 0.1044 0.8917 0.4876
conditions_df : pd.DataFrame, optional
Environmental conditions including temperature and relative humidity.
- `index`: pd.DateTimeIndex
- `columns`: (required)
- "temperature" [°C or K]
- "relative_humidity" [%]
Example::
timestamp temperature relative_humidity
2021-03-09 10:00:00 298.0 45.0
2021-03-09 11:00:00 303.0 50.0
2021-03-09 12:00:00 310.0 55.0
2021-03-09 13:00:00 315.0 60.0
temp_module : pd.Series, optional
Module temperatures [°C]. Required if `conditions_df` is not provided. Time indexed same as spectra_df
rh_module : pd.Series, optional
Relative humidity values [%]. Required if `conditions_df` is not provided. Time indexed same as spectra_df
Example::
30 = 30%
spectra : pd.Series type=Float
front or rear irradiance at each wavelength in "wavelengths" [W/m^2 nm]
rh_module : pd.Series type=Float
module RH, time indexed [%]
temp_module : pd.Series type=Float
module temperature, time indexed [C]
wavelengths : int-array
integer array (or list) of wavelengths tested w/ uniform delta
in nanometers [nm]
Ea : float
Arrhenius activation energy. The default is 40. [kJ/mol]
n : float
Expand All @@ -945,183 +908,58 @@ def degradation(
-------
degradation : float
Total degredation factor over time and wavelength.
"""
# --- TO DO ---
# unpack input-dataframe
# spectra = df['spectra']
# temp_module = df['temp_module']
# rh_module = df['rh_module']

# Constants
R = 0.0083145 # Gas Constant in [kJ/mol*K]

if conditions_df is not None and (temp_module is not None or rh_module is not None):
raise ValueError("Provide either conditions_df or temp_module and rh_module")
wav_bin = list(np.diff(wavelengths))
wav_bin.append(wav_bin[-1]) # Adding a bin for the last wavelength

if conditions_df is not None:
rh = conditions_df["relative_humidity"].values
temps = conditions_df["temperature"].values
else:
rh = rh_module.values
temps = temp_module.values

wavelengths = spectra_df.columns.values.astype(float)
irr = spectra_df.values # irradiance as array

# call numba compiled function
return deg(
wavelengths=wavelengths,
irr=irr,
rh=rh,
temps=temps,
Ea=Ea,
C2=C2,
p=p,
n=n,
C=C
)
# Integral over Wavelength
try:
irr = pd.DataFrame(spectra.tolist(), index=spectra.index)
irr.columns = wavelengths
except:
# TODO: Fix this except it works on some cases, veto it by cases
print("Removing brackets from spectral irradiance data")
# irr = data['spectra'].str.strip('[]').str.split(',', expand=True).astype(float)
irr = spectra.str.strip("[]").str.split(",", expand=True).astype(float)
irr.columns = wavelengths

# @njit
def deg(
wavelengths: np.ndarray,
irr: np.ndarray,
rh: np.ndarray,
temps: np.ndarray,
Ea: float,
C2: float,
p: float,
n: float,
C: float
) -> float:
sensitivitywavelengths = np.exp(-C2 * wavelengths)
irr = irr * sensitivitywavelengths
irr *= np.array(wav_bin)
irr = irr**p
data = pd.DataFrame(index=spectra.index)
data["G_integral"] = irr.sum(axis=1)

R = 0.0083145 # Gas Constant in [kJ/mol*K]
EApR = -Ea / R
C4 = np.exp(EApR / temp_module)

wav_bin = np.diff(wavelengths)
wav_bin = np.append(wav_bin, wav_bin[-1]) # Extend last bin

# inner integral
# wavelength d lambda
irr_weighted = irr * np.exp(-C2 * wavelengths) # weight irradiances
irr_weighted *= wav_bin
irr_pow = irr_weighted ** p
wavelength_integral = np.sum(irr_pow, axis=1) # sum over wavelengths
RHn = rh_module**n
data["Arr_integrand"] = C4 * RHn

# outer integral
# arrhenius integral dt
time_integrand = (rh ** n) * np.exp(-Ea / (R * temps))
data["dD"] = data["G_integral"] * data["Arr_integrand"]

dD = wavelength_integral * time_integrand
degradation = C * np.sum(dD)
degradation = C * data["dD"].sum(axis=0)

return degradation


# @deprecated("old double integral degradation function will be replaced 'pvdegradation' in an updated version of pvdeg")
# def degradation(
# spectra: pd.Series,
# rh_module: pd.Series,
# temp_module: pd.Series,
# wavelengths: Union[int, np.ndarray[float]],
# Ea: float = 40.0,
# n: float = 1.0,
# p: float = 0.5,
# C2: float = 0.07,
# C: float = 1.0,
# ) -> float:
# """
# Compute degredation as double integral of Arrhenius (Activation
# Energy, RH, Temperature) and spectral (wavelength, irradiance)
# functions over wavelength and time.

# .. math::

# D = C \\int_{0}^{t} RH(t)^n \\cdot e^{\\frac{-E_a}{RT(t)}} \\int_{\\lambda} [e^{-C_2 \\lambda} \\cdot G(\\lambda, t)]^p d\\lambda dt

# Parameters
# ----------
# spectra : pd.Series type=Float
# front or rear irradiance at each wavelength in "wavelengths" [W/m^2 nm]
# rh_module : pd.Series type=Float
# module RH, time indexed [%]
# temp_module : pd.Series type=Float
# module temperature, time indexed [C]
# wavelengths : int-array
# integer array (or list) of wavelengths tested w/ uniform delta
# in nanometers [nm]
# Ea : float
# Arrhenius activation energy. The default is 40. [kJ/mol]
# n : float
# Fit paramter for RH sensitivity. The default is 1.
# p : float
# Fit parameter for irradiance sensitivity. Typically
# 0.6 +- 0.22
# C2 : float
# Fit parameter for sensitivity to wavelength exponential.
# Typically 0.07
# C : float
# Fit parameter for the Degradation equaiton
# Typically 1.0

# Returns
# -------
# degradation : float
# Total degredation factor over time and wavelength.
# """
# # --- TO DO ---
# # unpack input-dataframe
# # spectra = df['spectra']
# # temp_module = df['temp_module']
# # rh_module = df['rh_module']

# # Constants
# R = 0.0083145 # Gas Constant in [kJ/mol*K]

# wav_bin = list(np.diff(wavelengths))
# wav_bin.append(wav_bin[-1]) # Adding a bin for the last wavelength

# # Integral over Wavelength
# try:
# irr = pd.DataFrame(spectra.tolist(), index=spectra.index)
# irr.columns = wavelengths
# except:
# # TODO: Fix this except it works on some cases, veto it by cases
# print("Removing brackets from spectral irradiance data")
# # irr = data['spectra'].str.strip('[]').str.split(',', expand=True).astype(float)
# irr = spectra.str.strip("[]").str.split(",", expand=True).astype(float)
# irr.columns = wavelengths


# # double integral calculation
# sensitivitywavelengths = np.exp(-C2 * wavelengths)
# irr = irr * sensitivitywavelengths
# irr *= np.array(wav_bin)
# irr = irr**p
# data = pd.DataFrame(index=spectra.index)
# data["G_integral"] = irr.sum(axis=1)

# EApR = -Ea / R
# C4 = np.exp(EApR / temp_module)

# RHn = rh_module**n

# data["Arr_integrand"] = C4 * RHn

# print("arr integral", data["Arr_integrand"])
# print("wavelength integral", data["G_integral"] )

# data["dD"] = data["G_integral"] * data["Arr_integrand"]

# print(f"delta degradation ", data["dD"])

# degradation = C * data["dD"].sum(axis=0)

# return degradation


# change it to take pd.DataFrame? instead of np.ndarray
@njit
def vecArrhenius(
poa_global: np.ndarray, module_temp: np.ndarray, ea: float, x: float, lnr0: float
) -> float:
"""
Calculate arrhenius degradation using vectorized operations. To eliminate the irradiance term set the irradiance sensitivity to 0.
.. math::
R_D = R_0 \\cdot I^X \\cdot e^{\\frac{-E_a}{kT}}
Calculates degradation using :math:`R_D = R_0 * I^X * e^{\\frac{-Ea}{kT}}`
Parameters
----------
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