Innovative metaheuristic algorithm with comparative analysis of MPPT for 5.5 kW floating photovoltaic system
Osama Elbaksawi, Nabil A.S. Elminshawy, Sodfa Diab, Ali M. Eltamaly, Amera Mahmoud, Hala Elhadidy
Abstract
Multiple localized maxima in power voltage features are triggered by non-uniform irradiance, which has a detrimental influence on photovoltaic (PV) system operation. Numerous control approaches for PV maximum power point tracking (MPPT) have lately been investigated. This paper proposes a metaheuristic algorithm to reach PV maximum power more efficiently based on the hybridization of Improved Grey Wolf Optimization (IGWO) and BAT algorithms, which are chosen for their reliability and fast MPPT for PV systems. However, they both encounter issues including delayed convergence and increased oscillations while tracking. To overcome these limitations, a newly Improved Grey Wolf BAT Optimization (IGWBO) is applied to specify the duty cycle parameter that is used in MPPT to enhance the performance of FPV systems under a variety of non-uniform weather scenarios. The results of implementing IGWBO-FPV are compared to those of IGWO-FPV, GWO-FPV, BAT-FPV, and FPV without any control algorithm. The findings revealed that the proposed IGWBO-FPV approach outperforms the annual generated power of the IGWO-FPV, GWO-FPV, BAT-FPV, and FPV without control by 5.64%, 10.58%, 17.54%, and 27.28% respectively. The optimal IGWBO-FPV enviro-economic evaluation indicates that 42.83 tons of CO 2 /year can be prevented from being released into the environment, with an LCOE of 0.052 $/kWh.