A novel sliding mode control and modified PSO-modified P&O algorithms for peak power control of PV

Photovoltaic (PV) energy is a renewable source which provides clean energy in power systems. Because of low efficiency of energy conversion in PV systems, harvesting maximum power from these systems is important. Many papers have been focused on this challenge to obtain the maximum power from PV array. Sliding mode control is an efficient control method to achieve maximum power. Although, due to non-linear curve of P-V and I-V of PV array in one side and uncertain PV generated power due to climate and temperature conditions, different evolutionary algorithms must be applied for accurate maximum power point tracking. Perturbation and observation (P&O) is a well-known method in this field but it has some defects in case of shadow-condition multiple maxima. In this paper, considering analysis of two sliding mode control structures, modified particle swarm optimization (PSO) algorithm has been used in combination with modified P&O method called modified PSO-modified P&O (MPSO-MP&O) to compensate the problem of P&O tracking in shadow conditions. The proposed method selects the global maximum point by searching all maximum points in many iterations. Also, the achievement stability of the maximum point is interesting in different temperature conditions and sudden changes of physical parameters of PV system. Simulation results show the efficiency of the proposed method performance in obtaining the maximum point faster with more PV power compared to other efficient methods in this field.