Partial shading detection for PV arrays in a maximum power tracking system using the sine-cosine algorithm

Abstract

This paper proposes a novel methodology for the detection of partial shading conditions in photovoltaic (PV) arrays based on the experience gained in the preliminary step of the detection algorithm. In the first stage of the problem, the periodic partial shading detection (PSD) problem is solved to detect the periodic partial shading condition (PSC) and to determine the optimal number of executing point of MPPT algorithm during PSC. The second stage of the PSD problem solves the maximum power point tracking (MPPT) problem to extract the maximum power from PV array at the executing point. The PSD problem is solved using the sine cosine algorithm (SCA) and to determine the global maximum operating point under various partial shading conditions, the improved sine cosine algorithm (ISCA) is proposed. The proposed method is guaranteed to find periodic shade and the global maximum operating point, avoiding the local operating point obstacle. Using MATLAB, the algorithm is implemented and tested in a simulation model. An experimental 2 kW PV system is developed to validate the operating point of the PV system under various partial shading patterns. The results demonstrate that the proposed algorithm outperforms the genetic algorithm and particle swarm optimization-based partial shading detection problem.