Abstract:

Isolated microgrids have demonstrated the possibility to be a sustainable resource of reliable energy, particularly in rural and remote locations. The integration of renewable power sources (RES) including solar and wind power into microgrids creates distinct challenges which stem from economic utilization of energy resources. The research focuses on solving the best dispatch problem for isolated microgrids which depend on renewable power sources through multiple solution methods. The research will assess the traditional optimization methods Linear Programming (LP) and Mixed Integer Linear Programming (MILP) against contemporary metaheuristic algorithms which include Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC). These findings indicate that even considering that renewable energy sources are stochastic, these algorithms are effective in reducing the operational costs and emissions and providing consistent electricity supply