Hardware-in-the-Loop Experimental Evaluation of MPPT Algorithms for Partially Shaded Photovoltaic Systems

Maximum power point tracking (MPPT) is a critical component of photovoltaic (PV) systems, as it ensures that the PV system operates at its maximum power output under varying conditions. Partial shading can significantly reduce the system's power generation. There are a variety of MPPT algorithms for PV systems but their performance may differ under partially shaded conditions. This paper conducted a hardware-in-the-loop (HIL) evaluation using the RTI DSpace 1104 card to assess two MPPT algorithms; Slime mould optimization (SMO) and Particle Swarm Optimization (PSO). the paper evaluated these algorithms under two shading scenarios, including uniform shading and dynamic shading conditions. The results of our HIL experiment demonstrated that SMO outperformed PSO in terms of the capability of stable tracking and convergence speed. SMO achieved an efficiency of over 60% improvement in tracking the MPP even in dynamic shading conditions. On the other hand, PSO showed susceptibility to tracking errors when faced with uniform shading conditions. These findings highlight SMO as an MPPT algorithm for PV systems, with shading challenges. It proves capable of efficiently tracking the Power Point even under demanding circumstances. The results of this research can help in choosing the MPPT algorithms for PV systems, under real-world conditions.