Environmentally Sustainable Clean Energy Solution: Optimizing Photovoltaic Systems Using the Gazelle-Nelder-Mead (GOANM) Algorithm

Abstract

The best ways to maximize electricity production in places where there is not enough room for the installation of renewable power generation systems are to optimize the operational efficiency of already-existing plants and select an optimal location for newly constructed Photovoltaic (PV) power plants that will offer a favorable climate and surrounding environment. Sustainable energy development strategies must be developed using renewable generation technologies to drive energy transition towards sustainability. Based on battery technology and energy storage assets, the study proposed a new hybrid Gazelle-Nelder-Mead (GOANM) algorithm for solar power storage solutions to satisfy the growing need for reliable and convenient renewable energy sources. This model looks at the sustainability of solar energy generation. At this crucial juncture, the research helps pave an intellectual and useful path toward a more promising and ecologically conscious future. It promotes solar energy as a clean, renewable energy source to mitigate climate change and severely cut carbon emissions. The study focuses on sustainable solar panel manufacturing methods, addressing issues with materials and industrial processes. The simulation result of the proposed GOANM algorithm highlights the importance of sustainable management methods and adequate site selection in mitigating the negative consequences of solar plant development.