Source code for pvlib.ivtools

# -*- coding: utf-8 -*-
"""
Created on Fri Mar 29 10:34:10 2019

@author: cwhanse
"""

import numpy as np
from scipy.optimize import root
from scipy import constants


[docs]def fit_sdm_cec_sam(celltype, v_mp, i_mp, v_oc, i_sc, alpha_sc, beta_voc, gamma_pmp, cells_in_series, temp_ref=25): """ Estimates parameters for the CEC single diode model (SDM) using the SAM SDK. Parameters ---------- celltype : str Value is one of 'monoSi', 'multiSi', 'polySi', 'cis', 'cigs', 'cdte', 'amorphous' v_mp : float Voltage at maximum power point [V] i_mp : float Current at maximum power point [A] v_oc : float Open circuit voltage [V] i_sc : float Short circuit current [A] alpha_sc : float Temperature coefficient of short circuit current [A/C] beta_voc : float Temperature coefficient of open circuit voltage [V/C] gamma_pmp : float Temperature coefficient of power at maximum point point [%/C] cells_in_series : int Number of cells in series temp_ref : float, default 25 Reference temperature condition [C] Returns ------- tuple of the following elements: * I_L_ref : float The light-generated current (or photocurrent) at reference conditions [A] * I_o_ref : float The dark or diode reverse saturation current at reference conditions [A] * R_sh_ref : float The shunt resistance at reference conditions, in ohms. * R_s : float The series resistance at reference conditions, in ohms. * a_ref : float The product of the usual diode ideality factor ``n`` (unitless), number of cells in series ``Ns``, and cell thermal voltage at reference conditions [V] * Adjust : float The adjustment to the temperature coefficient for short circuit current, in percent. Raises ------ ImportError if NREL-PySAM is not installed. RuntimeError if parameter extraction is not successful. Notes ----- Inputs ``v_mp``, ``v_oc``, ``i_mp`` and ``i_sc`` are assumed to be from a single IV curve at constant irradiance and cell temperature. Irradiance is not explicitly used by the fitting procedure. The irradiance level at which the input IV curve is determined and the specified cell temperature ``temp_ref`` are the reference conditions for the output parameters ``I_L_ref``, ``I_o_ref``, ``R_sh_ref``, ``R_s``, ``a_ref`` and ``Adjust``. References ---------- [1] A. Dobos, "An Improved Coefficient Calculator for the California Energy Commission 6 Parameter Photovoltaic Module Model", Journal of Solar Energy Engineering, vol 134, 2012. """ try: from PySAM import PySSC except ImportError: raise ImportError("Requires NREL's PySAM package at " "https://pypi.org/project/NREL-PySAM/.") datadict = {'tech_model': '6parsolve', 'financial_model': 'none', 'celltype': celltype, 'Vmp': v_mp, 'Imp': i_mp, 'Voc': v_oc, 'Isc': i_sc, 'alpha_isc': alpha_sc, 'beta_voc': beta_voc, 'gamma_pmp': gamma_pmp, 'Nser': cells_in_series, 'Tref': temp_ref} result = PySSC.ssc_sim_from_dict(datadict) if result['cmod_success'] == 1: return tuple([result[k] for k in ['Il', 'Io', 'Rsh', 'Rs', 'a', 'Adj']]) else: raise RuntimeError('Parameter estimation failed')
[docs]def fit_sde_sandia(voltage, current, v_oc=None, i_sc=None, v_mp_i_mp=None, vlim=0.2, ilim=0.1): r""" Fits the single diode equation (SDE) to an IV curve. Parameters ---------- voltage : ndarray 1D array of `float` type containing voltage at each point on the IV curve, increasing from 0 to ``v_oc`` inclusive [V] current : ndarray 1D array of `float` type containing current at each point on the IV curve, from ``i_sc`` to 0 inclusive [A] v_oc : float, default None Open circuit voltage [V]. If not provided, ``v_oc`` is taken as the last point in the ``voltage`` array. i_sc : float, default None Short circuit current [A]. If not provided, ``i_sc`` is taken as the first point in the ``current`` array. v_mp_i_mp : tuple of float, default None Voltage, current at maximum power point in units of [V], [A]. If not provided, the maximum power point is found at the maximum of ``voltage`` \times ``current``. vlim : float, default 0.2 Defines portion of IV curve where the exponential term in the single diode equation can be neglected, i.e. ``voltage`` <= ``vlim`` x ``v_oc`` [V] ilim : float, default 0.1 Defines portion of the IV curve where the exponential term in the single diode equation is signficant, approximately defined by ``current`` < (1 - ``ilim``) x ``i_sc`` [A] Returns ------- tuple of the following elements: * photocurrent : float photocurrent [A] * saturation_current : float dark (saturation) current [A] * resistance_shunt : float shunt (parallel) resistance, in ohms * resistance_series : float series resistance, in ohms * nNsVth : float product of thermal voltage ``Vth`` [V], diode ideality factor ``n``, and number of series cells ``Ns`` Raises ------ RuntimeError if parameter extraction is not successful. Notes ----- Inputs ``voltage``, ``current``, ``v_oc``, ``i_sc`` and ``v_mp_i_mp`` are assumed to be from a single IV curve at constant irradiance and cell temperature. :py:func:`fit_single_diode_sandia` obtains values for the five parameters for the single diode equation [1]: .. math:: I = I_{L} - I_{0} (\exp \frac{V + I R_{s}}{nNsVth} - 1) - \frac{V + I R_{s}}{R_{sh}} See :py:func:`pvsystem.singlediode` for definition of the parameters. The extraction method [2] proceeds in six steps. 1. In the single diode equation, replace :math:`R_{sh} = 1/G_{p}` and re-arrange .. math:: I = \frac{I_{L}}{1 + G_{p} R_{s}} - \frac{G_{p} V}{1 + G_{p} R_{s}} - \frac{I_{0}}{1 + G_{p} R_{s}} (\exp(\frac{V + I R_{s}}{nNsVth}) - 1) 2. The linear portion of the IV curve is defined as :math:`V \le vlim \times v_oc`. Over this portion of the IV curve, .. math:: \frac{I_{0}}{1 + G_{p} R_{s}} (\exp(\frac{V + I R_{s}}{nNsVth}) - 1) \approx 0 3. Fit the linear portion of the IV curve with a line. .. math:: I &\approx \frac{I_{L}}{1 + G_{p} R_{s}} - \frac{G_{p} V}{1 + G_{p} R_{s}} \\ &= \beta_{0} + \beta_{1} V 4. The exponential portion of the IV curve is defined by :math:`\beta_{0} + \beta_{1} \times V - I > ilim \times i_sc`. Over this portion of the curve, :math:`exp((V + IRs)/nNsVth) >> 1` so that .. math:: \exp(\frac{V + I R_{s}}{nNsVth}) - 1 \approx \exp(\frac{V + I R_{s}}{nNsVth}) 5. Fit the exponential portion of the IV curve. .. math:: \log(\beta_{0} - \beta_{1} V - I) &\approx \log(\frac{I_{0}}{1 + G_{p} R_{s}} + \frac{V}{nNsVth} + \frac{I R_{s}}{nNsVth} \\ &= \beta_{2} + beta_{3} V + \beta_{4} I 6. Calculate values for ``IL, I0, Rs, Rsh,`` and ``nNsVth`` from the regression coefficents :math:`\beta_{0}, \beta_{1}, \beta_{3}` and :math:`\beta_{4}`. References ---------- [1] S.R. Wenham, M.A. Green, M.E. Watt, "Applied Photovoltaics" ISBN 0 86758 909 4 [2] C. B. Jones, C. W. Hansen, Single Diode Parameter Extraction from In-Field Photovoltaic I-V Curves on a Single Board Computer, 46th IEEE Photovoltaic Specialist Conference, Chicago, IL, 2019 """ # If not provided, extract v_oc, i_sc, v_mp and i_mp from the IV curve data if v_oc is None: v_oc = voltage[-1] if i_sc is None: i_sc = current[0] if v_mp_i_mp is not None: v_mp, i_mp = v_mp_i_mp else: v_mp, i_mp = _find_mp(voltage, current) # Find beta0 and beta1 from linear portion of the IV curve beta0, beta1 = _find_beta0_beta1(voltage, current, vlim, v_oc) # Find beta3 and beta4 from the exponential portion of the IV curve beta3, beta4 = _find_beta3_beta4(voltage, current, beta0, beta1, ilim, i_sc) # calculate single diode parameters from regression coefficients return _calculate_sde_parameters(beta0, beta1, beta3, beta4, v_mp, i_mp, v_oc)
def fit_sdm_desoto(celltype, v_mp, i_mp, v_oc, i_sc, alpha_sc, beta_voc, cells_in_series, temp_ref=25, irrad_ref=1000): """ Calculates the five parameters for the single diode equation using the De Soto et al. procedure described in [1]. This procedure has the advantage of using common specifications given by manufacturers in the datasheets of PV modules. The six values returned by this function can be used by pvsystem.calcparams_desoto to calculate the values at different irradiance and cell temperature. Parameters ---------- celltype: str, case insensitive Value is one of 'monosi', 'multisi', 'polysi' or'gaas'. Others like 'cis', 'cigs', 'cdte', 'amorphous' are not implemented yet v_mp: numeric Module voltage at the maximum-power point at std conditions in V. i_mp: numeric Module current at the maximum-power point at std conditions in A. v_oc: numeric Open-circuit voltage at std conditions in V. i_sc: numeric Short-circuit current at std conditions in A. alpha_sc: numeric The short-circuit current (i_sc) temperature coefficient of the module in units of %/K. It is converted in A/K for the computing process. beta_voc: numeric The open-circuit voltage (v_oc) temperature coefficient of the module in units of %/K. It is converted in V/K for the computing process. cells_in_series: numeric Number of cell in the module. Optional input, but helps to insure the convergence of the computing. temp_ref: numeric, default 25 Reference temperature condition [C] irrad_ref: numeric, default 1000 Reference irradiance condition [W/m2] Returns ------- Dictionnary with the following elements: * 'I_L_ref': numeric Light-generated current in amperes at std conditions. * 'I_o_ref': numeric Diode saturation curent in amperes at std conditions * 'R_s': numeric Series resistance in ohms. Note that '_ref' is not mentionned in the name because this resistance is not sensible to the conditions of test. * 'R_sh_ref': numeric Shunt resistance in ohms at std conditions. * 'a_ref' : numeric Modified ideality factor at std conditions. The product of the usual diode ideality factor (n, unitless), number of cells in series (Ns), and cell thermal voltage at specified effective irradiance and cell temperature. * 'alpha_sc': numeric Caution!: Different from the input because of the unit. The short-circuit current (i_sc) temperature coefficient of the module in units of A/K. * 'EgRef': numeric Energy of bandgap of semi-conductor used (depending on celltype) [J] * 'dEgdT': numeric Variation of bandgap according to temperature [J/K] * 'irrad_ref': numeric Reference irradiance condition [W/m2] * 'temp_ref': numeric Reference temperature condition [C] References ---------- [1] W. De Soto et al., "Improvement and validation of a model for photovoltaic array performance", Solar Energy, vol 80, pp. 78-88, 2006. [2] John A Duffie ,William A Beckman, "Solar Engineering of Thermal Processes", Wiley, 2013 """ # Constants k = constants.Boltzmann # in J/K, or 8.617e-5 eV/K q = constants.elementary_charge # in J/V, or 1 eV Tref = temp_ref + 273.15 # in K if celltype.lower() in ['monosi', 'polysi', 'multisi', 'mono-c-si', 'multi-c-si']: dEgdT = -0.0002677 # valid for silicon EgRef = 1.796e-19 # in J, valid for silicon elif celltype.lower() in ['cis', 'cigs', 'cdte', 'amorphous', 'thin film']: raise NotImplementedError else: raise ValueError('Unknown cell type.') # Conversion from %/K to A/K & V/K alpha_sc = alpha_sc*i_sc/100 beta_voc = beta_voc*v_oc/100 def pv_fct(params, specs): """Returns the system of equations used for computing the single-diode 5 parameters. To avoid the confusion in names with variables of container function the '_' of the variables were removed. """ # six input known variables Isc, Voc, Imp, Vmp, betaoc, alphasc = specs # five parameters vector to find IL, Io, a, Rsh, Rs = params # five equation vector y = [0, 0, 0, 0, 0] # 1st equation - short-circuit - eq(3) in [1] y[0] = Isc - IL + Io*np.expm1(Isc*Rs/a) + Isc*Rs/Rsh # 2nd equation - open-circuit Tref - eq(4) in [1] y[1] = -IL + Io*np.expm1(Voc/a) + Voc/Rsh # 3rd equation - Imp & Vmp - eq(5) in [1] y[2] = Imp - IL + Io*np.exp((Vmp+Imp*Rs)/a) + \ (Vmp+Imp*Rs)/Rsh # 4th equation - Pmp derivated=0 - # caution: eq(6) in [1] seems to be incorrect, take eq23.2.6 in [2] y[3] = Imp - Vmp * ((Io/a)*np.exp((Vmp+Imp*Rs)/a) + 1.0/Rsh) / \ (1.0 + (Io*Rs/a)*np.exp((Vmp+Imp*Rs)/a) + Rs/Rsh) # 5th equation - open-circuit T2 - eq (4) at temperature T2 in [1] T2 = Tref + 2 Voc2 = (T2 - Tref)*betaoc + Voc # eq (7) in [1] a2 = a*T2/Tref # eq (8) in [1] IL2 = IL + alphasc*(T2-Tref) # eq (11) in [1] Eg2 = EgRef*(1 + dEgdT*(T2-Tref)) # eq (10) in [1] Io2 = Io * (T2/Tref)**3 * np.exp(1/k * (EgRef/Tref-Eg2/T2)) # eq (9) y[4] = -IL2 + Io2*np.expm1(Voc2/a2) + Voc2/Rsh # eq (4) at T2 return y # initial guesses of variables for computing convergence: # Values are taken from [2], p753 Rsh_i = 100.0 a_i = 1.5*k*Tref*cells_in_series/q IL_i = i_sc Io_i = i_sc * np.exp(-v_oc/a_i) Rs_i = (a_i*np.log1p((IL_i-i_mp)/Io_i) - v_mp)/i_mp # params_i : initial values vector params_i = np.array([IL_i, Io_i, a_i, Rsh_i, Rs_i]) # specs of module specs = np.array([i_sc, v_oc, i_mp, v_mp, beta_voc, alpha_sc]) # computing result = root(pv_fct, x0=params_i, args=specs, method='lm') if result.success: sdm_params = result.x else: raise RuntimeError('Parameter estimation failed') # results return {'I_L_ref': sdm_params[0], 'I_o_ref': sdm_params[1], 'a_ref': sdm_params[2], 'R_sh_ref': sdm_params[3], 'R_s': sdm_params[4], 'alpha_sc': alpha_sc, 'EgRef': EgRef, 'dEgdT': dEgdT, 'irrad_ref': irrad_ref, 'temp_ref': temp_ref} def _find_mp(voltage, current): """ Finds voltage and current at maximum power point. Parameters ---------- voltage : ndarray 1D array containing voltage at each point on the IV curve, increasing from 0 to v_oc inclusive, of `float` type [V] current : ndarray 1D array containing current at each point on the IV curve, decreasing from i_sc to 0 inclusive, of `float` type [A] Returns ------- v_mp, i_mp : tuple voltage ``v_mp`` and current ``i_mp`` at the maximum power point [V], [A] """ p = voltage * current idx = np.argmax(p) return voltage[idx], current[idx] def _calc_I0(IL, I, V, Gp, Rs, nNsVth): return (IL - I - Gp * V - Gp * Rs * I) / np.exp((V + Rs * I) / nNsVth) def _find_beta0_beta1(v, i, vlim, v_oc): # Get intercept and slope of linear portion of IV curve. # Start with V =< vlim * v_oc, extend by adding points until slope is # negative (downward). beta0 = np.nan beta1 = np.nan first_idx = np.searchsorted(v, vlim * v_oc) for idx in range(first_idx, len(v)): coef = np.polyfit(v[:idx], i[:idx], deg=1) if coef[0] < 0: # intercept term beta0 = coef[1].item() # sign change of slope to get positive parameter value beta1 = -coef[0].item() break if any(np.isnan([beta0, beta1])): raise RuntimeError("Parameter extraction failed: beta0={}, beta1={}" .format(beta0, beta1)) else: return beta0, beta1 def _find_beta3_beta4(voltage, current, beta0, beta1, ilim, i_sc): # Subtract the IV curve from the linear fit. y = beta0 - beta1 * voltage - current x = np.array([np.ones_like(voltage), voltage, current]).T # Select points where y > ilim * i_sc to regress log(y) onto x idx = (y > ilim * i_sc) result = np.linalg.lstsq(x[idx], np.log(y[idx]), rcond=None) coef = result[0] beta3 = coef[1].item() beta4 = coef[2].item() if any(np.isnan([beta3, beta4])): raise RuntimeError("Parameter extraction failed: beta3={}, beta4={}" .format(beta3, beta4)) else: return beta3, beta4 def _calculate_sde_parameters(beta0, beta1, beta3, beta4, v_mp, i_mp, v_oc): nNsVth = 1.0 / beta3 Rs = beta4 / beta3 Gp = beta1 / (1.0 - Rs * beta1) Rsh = 1.0 / Gp IL = (1 + Gp * Rs) * beta0 # calculate I0 I0_vmp = _calc_I0(IL, i_mp, v_mp, Gp, Rs, nNsVth) I0_voc = _calc_I0(IL, 0, v_oc, Gp, Rs, nNsVth) if any(np.isnan([I0_vmp, I0_voc])) or ((I0_vmp <= 0) and (I0_voc <= 0)): raise RuntimeError("Parameter extraction failed: I0 is undetermined.") elif (I0_vmp > 0) and (I0_voc > 0): I0 = 0.5 * (I0_vmp + I0_voc) elif (I0_vmp > 0): I0 = I0_vmp else: # I0_voc > 0 I0 = I0_voc return (IL, I0, Rsh, Rs, nNsVth)