Evolution of the shape parameters of photovoltaic module as a function of temperature and irradiance: New method of performance prediction without setting reference conditions
Hao Lu, Yunpeng Zhang, Peng Hao, Jiao Ma, Li Zhang, Tingkun Gu, Ming Yang
Abstract
The accurate characterization and prediction of current–voltage (I–V) characteristics of photovoltaic (PV) modules under different weather conditions are essential for solar power forecasting and ensuring grid stability. This paper proposed a novel method based on the power-law model (PLM) for estimating PV module performance under different weather conditions without setting reference conditions. The effects of solar irradiance, ambient temperature, and module types are all fully considered. The dependence of shape parameters in PLM on irradiance and temperature are thoroughly investigated and the effect of the selection of reference conditions is eliminated by modifying a set of new transforming equations. The parameters of the new transforming equations can be extracted from experimental data by an optimization algorithm. Due to the advantages of PLM, the proposed method applies to any type of PV module and the I–V characteristics can be expressed explicitly without Lambert W-function or iterative solution. The effectiveness and accuracy proposed method are verified and tested on the large datasets of eighteen PV modules in three locations. Compared with existing methods, the proposed method shows higher accuracy and better performance in the estimation of I–V characteristics and maximum power under different weather conditions.