diff --git a/pvdeg/degradation.py b/pvdeg/degradation.py index 7c9b85c..5845bae 100644 --- a/pvdeg/degradation.py +++ b/pvdeg/degradation.py @@ -13,7 +13,8 @@ from . import spectral from . import weather -from pvdeg.decorators import geospatial_quick_shape +from typing import Optional +from pvdeg.decorators import geospatial_quick_shape, deprecated # TODO: Clean up all those functions and add gaps functionality @@ -862,33 +863,70 @@ def _gJtoMJ(gJ): return MJ +# new version of degradation def degradation( - spectra: pd.Series, - rh_module: pd.Series, - temp_module: pd.Series, - wavelengths: Union[int, np.ndarray[float]], + spectra_df: pd.DataFrame, + conditions_df: pd.DataFrame = None, + temp_module: pd.Series = None, + rh_module: pd.Series = None, 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 : 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] + 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% + Ea : float Arrhenius activation energy. The default is 40. [kJ/mol] n : float @@ -907,58 +945,183 @@ 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] - 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 and (temp_module is not None or rh_module is not None): + raise ValueError("Provide either conditions_df or temp_module and rh_module") - # 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 + 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 + ) - 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) +@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: - EApR = -Ea / R - C4 = np.exp(EApR / temp_module) + R = 0.0083145 # Gas Constant in [kJ/mol*K] - RHn = rh_module**n - data["Arr_integrand"] = C4 * RHn + 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 - data["dD"] = data["G_integral"] * data["Arr_integrand"] + # outer integral + # arrhenius integral dt + time_integrand = (rh ** n) * np.exp(-Ea / (R * temps)) - degradation = C * data["dD"].sum(axis=0) + dD = wavelength_integral * time_integrand + degradation = C * np.sum(dD) 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: """ - Calculates degradation using :math:`R_D = R_0 * I^X * e^{\\frac{-Ea}{kT}}` + 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}} Parameters ---------- @@ -972,7 +1135,7 @@ def vecArrhenius( Activation energy [kJ/mol] x : float - Irradiance relation [unitless] + Irradiance sensitivity [unitless] lnR0 : float prefactor [ln(%/h)] diff --git a/tests/test_degradation.py b/tests/test_degradation.py index d9428e9..0454a01 100644 --- a/tests/test_degradation.py +++ b/tests/test_degradation.py @@ -131,12 +131,26 @@ def test_degradation(): data = pd.read_csv(INPUT_SPECTRA) wavelengths = np.array(range(280, 420, 20)) + + # convert to expected format + spectra = data["Spectra"] + spectra_df = pd.DataFrame(spectra.tolist(), index=spectra.index) + spectra_df = spectra.str.strip("[]").str.split(",", expand=True).astype(float) + spectra_df.columns = wavelengths + + conditions_df = pd.DataFrame( + index=spectra_df.index, + data={ + "relative_humidity": data["RH"], + "temperature": data["Temperature"], + } + ) + degradation = pvdeg.degradation.degradation( - spectra=data["Spectra"], - rh_module=data["RH"], - temp_module=data["Temperature"], - wavelengths=wavelengths, + spectra_df=spectra_df, + conditions_df=conditions_df ) + assert degradation == pytest.approx(4.4969e-38, abs=0.02e-38) diff --git a/tutorials_and_tools/tutorials_and_tools/3 - Spectral Degradation.ipynb b/tutorials_and_tools/tutorials_and_tools/3 - Spectral Degradation.ipynb index 91c048f..dce0356 100644 --- a/tutorials_and_tools/tutorials_and_tools/3 - Spectral Degradation.ipynb +++ b/tutorials_and_tools/tutorials_and_tools/3 - Spectral Degradation.ipynb @@ -32,22 +32,7 @@ "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\mspringe\\AppData\\Local\\Temp\\1\\ipykernel_40480\\1750438778.py:2: DeprecationWarning: \n", - "Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),\n", - "(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)\n", - "but was not found to be installed on your system.\n", - "If this would cause problems for you,\n", - "please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466\n", - " \n", - " import pandas as pd\n" - ] - } - ], + "outputs": [], "source": [ "import os\n", "import pandas as pd\n", @@ -66,9 +51,9 @@ "output_type": "stream", "text": [ "Working on a Windows 10\n", - "Python version 3.11.7 | packaged by Anaconda, Inc. | (main, Dec 15 2023, 18:05:47) [MSC v.1916 64 bit (AMD64)]\n", - "Pandas version 2.2.0\n", - "pvdeg version 0.2.4.dev83+ge2ceab9.d20240422\n" + "Python version 3.9.19 (main, May 6 2024, 20:12:36) [MSC v.1916 64 bit (AMD64)]\n", + "Pandas version 2.2.3\n", + "pvdeg version 0.4.3.dev22+g0ef212c.d20241017\n" ] } ], @@ -101,7 +86,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -201,6 +186,218 @@ "SPECTRA.head()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Convert To Expected Format**\n", + "\n", + "Since the original version of this tutorial, the expected inputs for the spectral degradation function have changed, we must convert the previously loaded inputs to the expected form. \n", + "\n", + "We will created the desired spectra dataframe and conditions dataframe in the following cell." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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"execution_count": 5, + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.496994351804118e-38" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "degradation = pvdeg.degradation.degradation(\n", + " spectra_df=spectra_df,\n", + " conditions_df=conditions_df\n", + ")\n", + "degradation" + ] + }, + { + "cell_type": "code", + "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Removing brackets from spectral irradiance data\n" + "Removing brackets from spectral irradiance data\n", + "arr integral timestamp\n", + "2021-03-09 10:00:00 2.193695e-45\n", + "2021-03-09 11:00:00 1.833548e-46\n", + "2021-03-09 12:00:00 1.508690e-34\n", + "2021-03-09 13:00:00 4.256451e-47\n", + "2021-03-09 14:00:00 1.041473e-82\n", + "2021-03-09 15:00:00 5.746285e-189\n", + "2021-03-09 16:00:00 2.430948e-62\n", + "2021-03-09 17:00:00 1.440645e-46\n", + "2021-03-09 18:00:00 2.196529e-64\n", + "2021-03-09 19:00:00 1.433768e-103\n", + "Name: Arr_integrand, dtype: float64\n", + "wavelength integral timestamp\n", + "2021-03-09 10:00:00 0.000358\n", + "2021-03-09 11:00:00 0.000287\n", + "2021-03-09 12:00:00 0.000298\n", + "2021-03-09 13:00:00 0.000258\n", + "2021-03-09 14:00:00 0.000338\n", + "2021-03-09 15:00:00 0.000412\n", + "2021-03-09 16:00:00 0.000275\n", + "2021-03-09 17:00:00 0.000309\n", + "2021-03-09 18:00:00 0.000311\n", + "2021-03-09 19:00:00 0.000284\n", + "Name: G_integral, dtype: float64\n", + "delta degradation timestamp\n", + "2021-03-09 10:00:00 7.861213e-49\n", + "2021-03-09 11:00:00 5.263019e-50\n", + "2021-03-09 12:00:00 4.496994e-38\n", + "2021-03-09 13:00:00 1.099005e-50\n", + "2021-03-09 14:00:00 3.519596e-86\n", + "2021-03-09 15:00:00 2.369241e-192\n", + "2021-03-09 16:00:00 6.696099e-66\n", + "2021-03-09 17:00:00 4.452817e-50\n", + "2021-03-09 18:00:00 6.827920e-68\n", + "2021-03-09 19:00:00 4.071628e-107\n", + "Name: dD, dtype: float64\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\tford\\AppData\\Local\\Temp\\2\\ipykernel_26040\\2414568496.py:1: DeprecationWarning: Call to deprecated function degradation (old double integral degradation function will be replaced 'pvdegradation' in an updated version of pvdeg).\n", + " degradation = pvdeg.degradation.degradation(spectra=SPECTRA['Spectra'],\n" ] + }, + { + "data": { + "text/plain": [ + "4.496994351804118e-38" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ "degradation = pvdeg.degradation.degradation(spectra=SPECTRA['Spectra'],\n", " rh_module=SPECTRA['RH'],\n", " temp_module=SPECTRA['Temperature'],\n", - " wavelengths=wavelengths)" + " wavelengths=wavelengths)\n", + "\n", + "degradation " ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "deg", "language": "python", "name": "python3" }, @@ -247,12 +524,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.7" - }, - "vscode": { - "interpreter": { - "hash": "14c04630f1cd445b2532d35c77825134bfcafda47af70d0b9c2b5023b1f357a5" - } + "version": "3.9.19" } }, "nbformat": 4,