Honey badger optimization algorithm based maximum power point tracking for solar photovoltaic systems

Solar photovoltaic systems are the most abundant renewable energy source and the cleanest type of solar-derived electrical energy. During the usage, the formation of multiple peaks is depicted in the P-V and I-V characteristics of the solar panels. Traditional Maximum Power Point Tracking (MPPT) algorithms fail to achieve the global peak power, due to multiple peaks, fluctuations, and slow tracking speed of the solar power. This paper proposes a novel metaheuristic Honey Badger Optimization (HBO) technique, for extracting global maxima from shaded panels. This algorithm's performance is compared to the conventional Perturb and Observe (P&O) and Particle Swarm Optimization (PSO) approach with less power loss, higher precision, fewer oscillations, and fewer iterations for three PV system topologies under partial shade situations. The analysis of five different module configurations in real-time applications has shown that the HBO method can achieve efficiency levels exceeding 97 percent.