LAUSR

This article presents a novel maximum point searching design for Photovoltaic (PV) systems using a Maximum Power Point Scanning (MPPS) technique. The MPPS is integrated into an online or off-line tester and finds out the Maximum Power Points (MPPs) automatically. The MPPS shows powerful sampling capacity with the hardware support—a Controlled Voltage Source (CVS). The performance of PV power sources controlled by the MPPS is studied under various partial shading conditions, and multiple MPPs are exhibited in Power-Voltage ($P-V$) and Current-Voltage ($I-V$) characteristic curves. Meantime, these curves reflect the “health” of the PV sources. The performance is mainly compared with two typical MPPT methods, namely the Perturb and Observe (P&O) method and the Group Searching Optimizer (GSO). The proposed MPPS algorithm is implemented on a PV system using MATLAB/SIMULINK. An experimental setup is also developed to verify the efficiency and accuracy of the proposed method. From the obtained simulation and experimental results, it is observed that the proposed MPPS algorithm outperforms the P&O method and the GSO.