Study on Probability Distribution of Photovoltaic Power Fluctuations at Multi-time Scales

Abstract

By analyzing the probability distribution function (p.d.f) of photovoltaic (PV) power, the influence of randomness and uncertainty of PV power fluctuation on the operation of power system can be effectively reduced. It will be beneficial to improve the PV grid-connected penetration. In this paper, the generalized Gaussian distribution, the finite student t-mixture model and other models are utilized to analyze the power fluctuation characteristics under multiple time scales, based on a large amount of data gathered from a distributed PV station. Firstly, the study shows that generalized Gaussian distribution performs best to describe the probability distribution of PV power variation and the average power variation under 10~15-min time scales while Gaussian mixture model performs best under 30~60-min time scales. Further, a model based on the relationship between the variability of hourly PV energy production and global solar radiation is proposed, which can be used for quantitative analysis of the energy production variability of PV stations.