Analysis and simulation of bio-inspired intelligent salp swarm MPPT method for the PV systems under partial shaded conditions

This paper proposes a new bio-inspired intelligence maximum power point tracking (MPPT) algorithm to abstract the high power from the photovoltaic (PV) array systems with the high tracking efficiency under partial shading conditions (PSC). The algorithm is based on the swarming behavior of salp, and this method locates global peak (GP) with the high convergence speed and high efficiency. The proposed salp swarm (SS) algorithm reduces the computational time than the conventional MPPT algorithms such as whale optimization (WO) algorithm, and perturb and observation (PO) algorithm discussed in the literature. The modeling and simulation is done with Matlab software and validated under PSCs. The simulation result demonstrates the effectiveness of SS algorithm with high tracking efficiency and the high convergence to GP.