Grey Wolf Optimisation for Optimal Generation Scheduling of Distributed Energy Resources in Microgrid

Integrating the Distributed Energy Resources (DERs) into the modern power system requires intelligent scheduling algorithms for stability, reliability and cost effectiveness. This paper analyses the optimal generation scheduling in a microgrid consisting of photovoltaic (PV) systems, wind turbines (WTs), diesel generators (DGs) and battery energy storage systems (BESSs). Evolutionary optimisation algorithm, namely Grey Wolf Optimisation (GWO), is employed to minimise the total generation cost of the system while considering the constraints like power balance, generator ramp limits and state of charge (SOC) of battery dynamics. Simulations are done in a CIGRE LV 18 bus microgrid using MATLAB 2024, and the results are reported. Comparison with GA results shows that GWO has faster convergence and produces smoother generator and battery schedules, with a reduction in operational stress.