Analytical modeling and parameter estimation of photovoltaic strings under partial shading conditions

Abstract

An accurate estimation of the photovoltaic (PV) electrical characteristics is of significance to the decision-making related to the establishment and operation of PV systems. However, most of the existing PV models are very limited to predicting the PV behaviors under uniform irradiation conditions (UICs). This paper proposes a complete solution to modeling and simulation of PV strings under partial shading conditions (PSCs). The measured current-voltage ( I–V ) data are first characterized by a shading information matrix containing essential environmental conditions for operating points. The model parameters are estimated via a four-state Jaya (FSJ) algorithm, which applies an exploration-exploitation adaptation mechanism to make an appropriate trade-off between global and local searching efforts. Fed by the obtained shading information and optimal parameters, the “staircase” shape I–V curve can be accurately predicted via a comprehensive analytical PV model. The experimental results are tested on two different PV strings with multi-crystalline and mono-crystalline PV technologies. Results suggest that the proposed FSJ algorithm outperforms reported state-of-the-art optimization algorithms in terms of convergence speed and prediction errors. With the optimal parameters, the analytical PV model gives superior results under various PSCs. The proposed model and algorithms can serve as an efficient alternative for modeling PV strings. • A shading information matrix is used to characterize the current-voltage characteristics of a photovoltaic (PV) string. • An analytical modeling method is proposed to predict a PV string's current under partial shading conditions. • A four-state Jaya mechanism improves the model's predictive accuracy. • The individual difference and generation gap are used to identify the state of a parameter estimation process. • The proposed analytical model outperforms the existing commercial simulation tools.