PVLife: An Integrated Model for Predicting PV Performance Degradation over 25+ Years Mark A. Mikofski, David F. J. Kavulak, David Okawa, Yu-Chen Shen, Akira Terao, Michael Anderson, Sander Caldwell, Doug Kim, Nicholas Boitnott, Junrhey Castro, Laurice Ann Laurio Smith, Ryan Lacerda, Dylan Benjamin and Ernest F. Hasselbrink Jr. SunPower Corporation, 77 Rio Robles, San Jose, CA 95134, USA Abstract — We report results of an integrated model called PVLife that predicts the performance and degradation of a PV system over its entire lifetime. The model solves the coupled electro-thermal equations to calculate PV panel performance for a given set of weather conditions. Based on this calculated operating point and a series of physical sub-models for key degradation and failure modes, the progressive degradation of the panel performance is simulated, creating a second level of coupling. The sub-models describing the different degradation modes are developed based on data from the field and accelerated laboratory tests. To close the loop, the overall model is compared with both laboratory and field data. Coupled degradation modes, including possible feedback loops, are investigated. Index Terms — degradation, modeling, performance, reliability, simulation. I. INTRODUCTION Warranties of 25 years are the norm in the solar industry, yet data to support this reliability requirement have never been fully integrated into a complete physical model. In this paper we report results of an integrated model called PVLife that not only solves the coupled electro-thermal equations that predict panel performance for a given set of weather conditions, but also incorporates physical sub-models for key degradation and failure modes that govern panel lifetime performance. Inputs to the model include weather data and cell-level electrical and thermal parameters. The model independently computes the incident spectrum, electrical operating point and temperature of each individual cell at each timestep over the module lifetime simulated. Based on computed electrical state and temperature, the incremental degradation during each timestep is computed using multiple physical sub-models. Degradation modes, such as UV-induced cell degradation and encapsulant browning, are computed using models based on test data. Failure probabilities due to binary “end of life” events are also calculated. The model is compared with laboratory and field data obtained from various SunPower product monitoring efforts. II. ELECTRICAL/THERMAL MODEL We recently described a 1-diode model [1], which offers accurate results but has implicit temperature dependence [2] that requires a substantial amount of computational time. The electrical model has been upgraded to a 2-diode model with explicit temperature dependence [3]-[5], which retains accuracy but reduces computation time by reducing the number of equations and unknowns when searching for the maximum power point (MPP) at each timestep. Each cell in a module is modeled as a photo-generated current source in parallel with two diodes and a shunt resistor, all in series with another resistor as depicted in Fig. 1. Fig. 1. The 2-diode model of a solar cell. The photo-generated current, I ph , is proportional to the irradiance and is normalized by the short circuit current at standard test conditions (STC), I sc,0 . ,0 ph ph sc e I AI E = (1) The effective irradiance in suns, E e , takes into account angle of incidence (AOI), transmission through the glass and encapsulant and spectral response of the cell. The proportionality factor, A ph , depends weakly on E e and cell temperature T cell , and is generally very close to one. The current through the diodes, I diode , is modeled using the familiar Shockley diode equation. exp 1 cell cell s diode sat T V I R I I mV     + = −         (2) In (2), the saturation current, I sat , is a strong function of T cell [4][5]. The cell voltage and current are given by V cell and I cell respectively. It can be seen in Fig. 1 that the voltage across the diode, V diode , equals V cell + I cell R s , where R s is the series resistance, which varies directly with T cell . The thermal voltage, V T , is related to T cell , Boltzmann’s constant, k, and an elementary charge, q, as in (3) below. T cell V kT q = (3)