IoT-enabled Rapid Global Maximum Power Point Tracking for Multiple Photovoltaic Inverters

Maximum power point tracking (MPPT) is a crucial technology for enhancing photovoltaic (PV) array power generation efficiency. Under scenarios with partial shading, the output power characteristic curve of a PV array often displays multiple peaks, necessitating the use of global peak-seeking techniques. Particle Swarm Optimization (PSO) and its advanced variants have been widely adopted to address global optimization challenges. However, the current landscape primarily includes PSO based MPPT methods designed for single inverters, which tend to exhibit slow optimization speeds. This paper presents an Internet of Things (IoT)-based multi-inverters approach for global MPPT. In this approach, all inverters within the network are treated as a single particle. This transformation shifts the conventional serial PSO operation into a parallel one, enabling data exchange among inverters to jointly track the maximum power point. Simulation results demonstrate that the proposed methodology significantly accelerates the optimization process, effectively mitigating the limitations of traditional approaches.