An Efficient Ant Colony Optimization Approach for MPPT in Solar Photovoltaic Applications Under Shading Effects

Mukul Pal

Abstract: Partially shaded PV devices show very non-linear and multimodal PV power-voltage characteristics which include multiple local maxima, making it very challenging to achieve an effective MPPT. It is well known that the deterministic MPPT and heuristic MPPTs both converge to sub-optimum operating point, thereby reducing the amount of energy generated by the system and the efficiency of the system. In this paper, a novel model of Ant Colony Optimization inspired global maximum extraction algorithm for PV systems under non-uniform irradiation is presented which overcomes these drawbacks under non-uniform irradiation is presented which overcomes these drawbacks. In the proposed approach, formulation of the MPPT problem is a constrained optimization problem with the duty cycle of the DC-DC converter as the optimization variable, and the instantaneous PV output power as the optimization objective. In order to keep a balance between exploration and exploitation, ACO algorithm adopts the probabilistic solution construction and the adaptive pheromone updating method and continuously narrows the search space. It features a memory-assisted duty cycle update mechanism that enhances the smoothness of convergence and minimizes oscillatory behavior at the optimum operating point. The suggested controller is strictly tested in terms of dynamically changing partial shading patterns, taking into account the fast irradiance changes and multiple peak conditions. The findings show that convergence reliability is better, global maximum identification time is lower and steady-state power oscillations are lower than those in conventional and modern MPPT methods. Moreover, the suggested approach is also very robust and flexible, which makes it very applicable to become part of smart energy management systems and advanced DC micro grid designs.

Keywords: Photovoltaic, Maximum power point tracking, Global maximum power point, Hybrid, Optimization, Partial shading condition, Ant colony optimization