Design and analysis of a PSO controlled four-phase interleaved boost converter

Photovoltaic (PV) systems, which convert solar energy into electricity through irradiation, play a crucial role in renewable energy generation. To ensure these systems operate efficiently and maximize power output, Maximum Power Point Tracking (MPPT) is essential. Numerous algorithms have been developed to optimize MPPT, one of which is the metaheuristic Particle Swarm Optimization (PSO) inspired by swarm intelligence. Boost converters are used to increase and regulate the voltage and current output of PV panels, ensuring they operate at the MPP under varying irradiation and temperature conditions. In addition to the PSO algorithm, a four-phase interleaved boost converter has been utilized in this thesis, distinguishing it from conventional studies. This technology, which enables switching elements to operate differently across phases, allows for switching much higher power levels compared to ordinary topologies. Simulations and experimental result verify (confirm validate) that the proposed integration exhibits superior performance over traditional MPPT techniques, thanks to its repetitive duty cycle control and precise power measurement capabilities. Through these features, a stable algorithm controlling the four-phase interleaved boost converter has been achieved with an average efficiency of 98% under varying irradiance conditions.