A hybrid of bio-inspired algorithm based on Levy flight and particle swarm optimizations for photovoltaic system under partial shading conditions

•Modelling and simulation of solar MPPT under partial shading conditions.•A hybrid bio-inspired LPSO algorithm is proposed.•LPSO is compared with PSO and LFO under steady-state and dynamic conditions.•LPSO algorithm has advantages in terms of zero oscillation, stable and fast tracking. In this paper, a hybrid of bio-inspired control algorithm to track the maximum power point of photovoltaic (PV) system under partial shading conditions is proposed. Particle swarm optimization (PSO) is a well-known method due to its simplicity and ease of implementation. Levy flight optimization (LFO) is a random walk distribution which is also simple and able to provide fast response. In the proposed algorithm, these two methods are integrated together, noted as a hybrid of Levy flight and particle swarm optimization (LPSO) to extract the global maximum power point (GMPP). The proposed LPSO is evaluated under three conditions: (1) under uniform irradiance (2) under non-uniform irradiance and (3) under step-change of irradiance. A prototype is built to verify the effectiveness of the proposed LPSO. Based on the results obtained, it clearly shows that the hybrid LPSO can track the local and global maximum power point effectively. Both simulation and experimental results show that the proposed LPSO is stable and efficient with zero steady-state oscillation. The efficiency of the proposed LPSO is approximately 99.50% for all tested conditions.