Publication

Abstract : In today's world, one can witness various developing advancements in Smart Grid (SG) technologies and one of these major advancements is load balancing. Load balancing involves the equitable distribution of resources to ensure optimal performance and efficiency within a system, such as a network or power grid, which aims at maximizing utilization. Taking into consideration a microgrid which is made up of local energy sources like solar panels, wind turbines, or batteries, along with control systems to manage the flow of electricity and also the potential for renewable energy integration thereby seeking energy independence and sustainability. In this paper, better management of generation scheduling in a microgrid is carried out by stochastic optimization techniques. To investigate the PV and wind energy generation, optimal generation scheduling based on the availability is monitored and scheduled using the Particle Swarm Optimization (PSO) technique, and a Fuzzy Logic Controller is used. The best technique to identify and schedule the generation based on the optimal and faster performance is validated using MATLAB/Simulink. The performance of two techniques based on accuracy is proposed for the benefit of being adapted in real-time usage.