Enhanced leader adaptive velocity particle swarm optimisation based global maximum power point tracking technique for a PV string under partially shaded conditions

Under partially shaded conditions (PSC), obtaining the global maximum on the multi-peak power-voltage (P-V) curve by particle swarm optimisation (PSO) method requires proper tuning of parameters to avoid premature convergence problems. In this study, a new fast tracking global maximum power point tracking (GMPPT) technique for a photovoltaic (PV) string under PSC is proposed. The proposed GMPPT technique has the advantages of two PSO techniques: leader PSO (LPSO) and adaptive velocity PSO (AVPSO). The proposed enhanced leader adaptive velocity PSO (ELAVPSO) GMPPT technique overcomes the limitations of conventional PSO such as premature convergence and difficulty in parameter tuning. Furthermore, a new shading detection scheme is proposed, which accurately finds the type of shading from P-V curve scanning. With the proposed scheme, ELAVPSO GMPPT method is used only to find the global maximum power point during PSC and perturb & observe algorithm is used for maximum power point tracking during uniform irradiance. Under PSC, the limits of the search space of the proposed GMPPT technique can be identified at the time of curve scanning. The proposed algorithm is simulated and experimentally validated by using a boost direct current-direct current (DC-DC) converter prototype.