Impact of duration and missing data on the long-term photovoltaic degradation rate estimation. (January 2022)

• Record Type: Journal Article
• Authors: Romero-Fiances, Irene; Livera, Andreas; Theristis, Marios; Makrides, George; Stein, Joshua S.; Nofuentes, Gustavo; de la Casa, Juan; Georghiou, George E.
• Is Part Of: Renewable energy. Volume 181(2022)
• Page Start: 738
• Page End: 748
• Publication Date: 2022-01
• Subjects: Missing data -- Degradation rate -- Performance -- Photovoltaic -- Time series duration; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2021.09.078
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: Accurate quantification of photovoltaic (PV) system degradation rate ( R D ) is essential for lifetime yield predictions. Although R D is a critical parameter, its estimation lacks a standardized methodology that can be applied on outdoor field data. The purpose of this paper is to investigate the impact of time period duration and missing data on R D by analyzing the performance of different techniques applied to synthetic PV system data at different linear R D patterns and known noise conditions. The analysis includes the application of different techniques to a 10-year synthetic dataset of a crystalline Silicon PV system, with emulated degradation levels and imputed missing data. The analysis demonstrated that the accuracy of ordinary least squares (OLS), year-on-year (YOY), autoregressive integrated moving average (ARIMA) and robust principal component analysis (RPCA) techniques is affected by the evaluation duration with all techniques converging to lower R D deviations over the 10-year evaluation, apart from RPCA at high degradation levels. Moreover, the estimated R D is strongly affected by the amount of missing data. Filtering out the corrupted data yielded more accurate R D results for all techniques. It is proven that the application of a change-point detection stage is necessary and guidelines for accurate R D estimation are provided.