Experimental validation of a novel previous proposed MPPT control strategy based on a weighting mechanism for enhanced photovoltaic system efficiency

Abstract

Simulation is a crucial step for analyzing and verifying system behavior prior to implementation on real hardware. However, experimental validation remains necessary to assess system performance under real operating conditions, which involve constraints that are difficult to accurately model in simulation. In this context, this paper presents the experimental validation of a novel maximum power point tracking (MPPT) algorithm based on a weighting mechanism that enables adaptive step-size computation. In the first stage, the proposed algorithm was first evaluated through Hardware-in-the-Loop (HIL) tests using the TMS320F28377S real time microcontroller control board and the MATLAB/Simulink environment. Under standard test conditions, the algorithm achieved a response time five times faster and an efficiency of 99.96%, while reducing steady-state power oscillations by more than 90% compared to the conventional Perturb and Observe (P&O) algorithm. Furthermore, under varying illumination conditions, it demonstrated superiority over the P&O method in maximum power point (MPP) tracking, as well as reliable convergence to the global maximum power point (GMPP) under partial shading. In the second stage, experimental tests were conducted on photovoltaic (PV) system with a maximum power of 285 W and a MPP voltage of 31.64 V, confirming the algorithm’s performance under real operating conditions. The experimental results validity of the simulation findings, demonstrating fast convergence to the MPP, a significant reduction in power oscillations, and enhanced steady-state stability.