Optimal Sizing and Placement of Solar PV and Battery Energy Storage in a Microgrid Using Metaheuristic Algorithms

Abstract

The rapid growth in global energy demand, combined with increasing environmental concerns and the depletion of conventional fossil fuel resources, has accelerated the transition toward renewable energy-based power systems. Among various renewable technologies, Solar Photovoltaic (PV) systems have emerged as one of the most widely adopted solutions due to their sustainability, low operating cost, and abundant availability. However, the intermittent and variable nature of solar energy introduces significant challenges in maintaining power system stability, reliability, and continuous power supply.  The proposed GA–PSO hybrid optimization framework provides an effective, robust, and efficient solution for the optimal sizing and placement of Solar PV and BESS in microgrid systems. It successfully addresses the challenges associated with renewable energy integration by achieving an optimal balance between economic, technical, and reliability objectives. The study demonstrates that hybrid metaheuristic algorithms are highly suitable for complex power system optimization problems and can significantly contribute to the development of sustainable, reliable, and intelligent smart grid systems. The proposed methodology can be extended in future work by incorporating additional renewable sources, electric vehicles, demand response programs, and real-time implementation using advanced computational platforms.