Photovoltaic arrays subject to partial shading conditions have more than one maximum power point (MPP), and conventional algorithms are unable to track the global maximum power point (GMPP) accurately. Thus, an improved global search space differential evolution algorithm for tracking the GMPP is introduced in this paper. The main contribution of the proposed algorithm are: a) capability in tracking GMPP and faster respond against load variation, b) optimization algorithm can search for the GMPP within a larger operating region as it is implemented by using a single-ended primary-inductor converter, c) easy tuning as less parameter has to be set in the algorithm. The proposed system is first simulated in MATLAB to ensure its capability. The feasibility of the approach is validated through physical implementation and experimentation. Results demonstrate that the proposed algorithm has the capability to track the GMPP within 2 s with an accuracy of 99% and respond to load variation within 0.1 s.

In photovoltaic (PV) power generation, partial shading is an unavoidable complication that significantly reduces the efficiency of the overall system. Under this condition, the PV system produces a multiple-peak function in its output power characteristic. Thus, a reliable technique is required to track the global maximum power point (GMPP) within an appropriate time. This study aims to employ a hybrid evolutionary algorithm called the DEPSO technique, a combination of the differential evolutionary (DE) algorithm and particle swarm optimization (PSO), to detect the maximum power point under partial shading conditions. The paper starts with a brief description about the behavior of PV systems under partial shading conditions. Then, the DEPSO technique along with its implementation in maximum power point tracking (MPPT) is explained in detail. Finally, Simulation and experimental results are presented to verify the performance of the proposed technique under different partial shading conditions. Results prove the advantages of the proposed method, such as its reliability, system-independence, and accuracy in tracking the GMPP under partial shading conditions.