A Novel Global Maximum Power Point Tracking Technique based on Shading Detection for Photovoltaic Strings

Abstract

Multiple peaks in power-voltage (P-V) characteristics of photovoltaic (PV) strings under partial shading conditions (PSC) bring challenges to maximum power point tracking (MPPT) techniques for reaching the global maximum power point (GMPP). Early studies have revealed that the locus of the GMPP can be predicted from the shading information, which is the mathematical indicator to express the PSC. In this paper, a novel global maximum power point tracking (GMPPT) method based on the detection of the shading vector is proposed in this paper. The locus of the GMPP is estimated from the peak matrix transformed by shading vector. Simulation results demonstrate that the proposed GMPPT method is capable of tracking the GMPP efficiently under various shading patterns. By comparing with the original $\mathbf{0.8\mathbf{V}_{\mathbf{OC}}}$ -model-based MPPT method, the proposed method reduces the tracking step by 75% while maintaining good prediction accuracy.