Remaining Life Prediction Method for Photovoltaic Modules Based on Two-Stage Wiener Process  

作　　者：Jie Lin Hongchi Shen Tingting Pei Yan Wu 

机构地区：[1]School of Electrical Engineering and Information Engineering,Lanzhou University of Technology,Lanzhou,730050,China

出　　处：《Energy Engineering》2025年第1期331-347,共17页能源工程（英文）

基　　金：supported by the National Natural Science Foundation of China(51767017);the Basic Research Innovation Group Project of Gansu Province(18JR3RA133);the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).

摘　　要：Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.

关 键 词：Photovoltaic modules DEGRADATION stochastic processes lifetime prediction 

分 类 号：TM615[电气工程—电力系统及自动化]