Photovoltaic Systems Degradation Modeling Under Dynamic Environmental Profiles

Reliability question of photovoltaic (PV) systems attracts significant attention due to performance degradation resulting from environment stresses. Different from monotone performance characteristics, such as wear and crack sizes, the power output of PV systems periodically degrades and is autocorrelated. Based on these considerations, we propose a semi-parametric model with autoregressive moving average (ARMA) model to extract the degradation rates of PV systems in this paper. Multivariate Bernstein bases with shape constraints are used to study interactions of time-varying covariates. The block coordinate descent method that jointly implements the quadratic optimization algorithm and nonlinear least square algorithm is used to estimate unknown parameters. Finally, different ground PV systems are provided to illustrate the effectiveness of the proposed method in practice.