Distribution‐based PV module degradation model

Author:

Lai Guangzhi1,Wang Dong1,Wang Ziyue2,Fan Fu3,Wang Qihang4ORCID,Wang Ruyi4

Affiliation:

1. State Grid e‐commerce Co., Ltd Beijing China

2. State Grid Tianjin Electric Power Company Tianjin China

3. School of Computer Science and Technology Beijing Institute of Technology Beijing China

4. School of Automation Southeast University Nanjing China

Abstract

AbstractThe degradation of photovoltaic modules has an impact on various parameters of photovoltaic modules. Ignoring the degradation of photovoltaic modules or inaccurate estimation of the degradation will lead to wrong power dispatching strategies and lead to economic losses. For PV module life estimation or reliability estimation, it is necessary to first establish an accurate statistical degradation model of PV module. The main goal of this paper is to analyze a selection of explicit PV module degradation model based on distribution. Since the degradation is related to time, the study assumed that those parameters in Gamma or Gaussian distributions are related to time. Five models are calculated based on maximum likelihood estimation and particle swarm optimization. Through verification and comparison on the measured PV module degradation data, the performance of these models in four cases: long‐term data fitting, long‐term data prediction, single‐module short‐term data fitting, and multimodule short‐term data fitting are evaluated. The results show that the model proposed in this paper has a great improvement over the original model, and the constant‐σ Gaussian distribution degradation model achieves the best performance.

Publisher

Wiley

Subject

General Energy,Safety, Risk, Reliability and Quality

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