Optimization of Hybrid Wind–Solar Energy System with Battery Storage for Large-Scale Grid Integration

Abstract

The increasing penetration of renewable energy sources in modern power systems necessitates efficient and reliable solutions for large-scale grid integration. Hybrid wind–solar energy systems have emerged as a promising approach due to the complementary nature of wind and solar resources. However, their intermittent and variable output poses significant challenges in maintaining grid stability and ensuring continuous power supply. To address these issues, the integration of battery energy storage systems (BESS) along with optimized system design has become essential. This study presents an optimization framework for a hybrid wind–solar energy system integrated with battery storage aimed at large-scale grid applications. The proposed approach focuses on optimal sizing and configuration of system components, including wind turbines, photovoltaic arrays, and battery storage, to achieve maximum efficiency, reliability, and cost-effectiveness. Advanced optimization techniques such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) are employed to minimize power fluctuations, reduce operational costs, and enhance system performance. Furthermore, the study incorporates intelligent energy management strategies to ensure effective coordination between generation, storage, and load demand. Simulation results demonstrate that the optimized hybrid system significantly improves power quality, reduces energy curtailment, and enhances grid stability compared to conventional standalone renewable systems. The findings highlight the critical role of optimization and battery storage in enabling the large-scale deployment of hybrid renewable energy systems, contributing to a sustainable and resilient power infrastructure