Hybrid Global Maximum Power Tracking Method With Partial Shading Detection Technique for PV Systems

Abstract

The conventional maximum power point tracking (MPPT) controllers are unable to track the global maximum power point (GMPP) during partial shading conditions (PSCs). As a result, many optimization strategies have been used to track the GMPP. Optimization approaches, on the other hand, are iterative methods that cannot distinguish uniform shading conditions (USCs) from PSCs. In this article, a new partial shading detection approach has been hybridized with the new modified rat swarm optimization (MRSO) algorithm. It successfully distinguishes USCs from PSCs in two samples and triggers the MRSO only when the PSC is detected. Consequently, it avoids the excessive global peak search during the USCs, which improves the tracking time for USCs without an unnecessary scan of the entire <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$P$ </tex-math></inline-formula> – <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula> curve. Furthermore, the proposed MRSO is simple to implement with simple tuning parameters and fast-tracking speed for PSCs. The proposed method has been experimentally validated on a boost converter with a sampling time of 0.05 s. The experimental results showed the successful implementation of the proposed method with an average tracking time for uniform and PSCs of 0.42 s with an average steady-state efficiency of 99.8%. Subsequently, a comparison with state-of-the-art methods in this domain has been provided to assess the efficacy of the proposed method.