Efficient Maximum Power Point Tracking Algorithm for Photovoltaic Systems under Partial Shading Conditions: Hybrid FSSO-HHO Approach with Hardware-in-Loop Validation

Abstract Solar energy has attended an extensive acceptance for its ability to generate electricity and eco-friendly nature, which is beneficial to the environment and prevents harmful effects due to the use of fossil fuels. Power generation from solar resources is definitely a boon, but it is liable to its availability and variation due to changing factors such as irradiation, temperature, shading conditions, etc. The economic feasibility of this system is also dependent on its operating conditions. Maximum Power Point Tracking (MPPT) has been used in different ways to lessen the effect of atmospheric changes. Partial shading conditions (PSC) are one of the major causes of the MPP change in photovoltaic systems. There are utmost algorithms suggested to track the global peak, but due to certain factors, they are unable to track it successfully under PSCs. This conventional MPPT control technique has some crucial routine drawbacks, such as high tracking, settling times and oscillations at global maxima (GM) under PSC. This paper proposes a metaheuristic optimisation algorithm utilising hybrid FSSO (Flying Squirrel Search Optimisation) with HHO (Harris Hawks Optimizer) MPPT technique methods under different PSCs to ensure regulated, efficient power delivery, less complexity, cost effectiveness, easy hardware implementation, high accuracy, and almost zero oscillation near GM. The proposed algorithm is tested using Hard-ware-in-loop (HIL) setup. The proposed algorithm gives 99.99% tracking efficiency for all four partial shading conditions. The efficacy of the proposed algorithm is overall superior compared to other methods in terms of statistical analysis and tracking time.