Harnessing Particle Swarm Optimization for Smarter Energy Distribution in Microgrids

Recent innovations in the energy sector due to increased demand for sustainable sources of energy have been realized through the development of Multi-energy Microgrids (MEMGs) to address electrical and thermal energy from renewable and non-renewable resources. Presenting a dynamic MEMG model within the context of energy distribution improvement, this paper introduces a Particle Swarm Optimization (PSO). Optimizes energy flow and enhances the utilization of renewable energy to help attain least dependency on outer grids, losses, and overhead. Using MATLAB simulations and real time hardware implementation, the authors have demonstrated that the proposed system reduces energy losses by 30%, cuts costs by a quarter and raises efficiency by 20%. Furthermore, renewable energy utilization is also improved by 40% eradicating the impacts of carbon footprint. This paper also presents that using PSO-based EMS to optimize energy consumption can achieve energy sustainability in buildings, and it provides the potential solutions for the future large-scale applications of energy management systems.