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As global attention on renewable and clean energy grows, the research andimplementation of microgrids become paramount. This paper delves into themethodology of exploring the relationship between the operational andenvironmental costs of microgrids through multi-objective optimization models.By integrating various optimization algorithms like Genetic Algorithm,Simulated Annealing, Ant Colony Optimization, and Particle Swarm Optimization,we propose an integrated approach for microgrid optimization. Simulationresults depict that these algorithms provide different dispatch results undereconomic and environmental dispatch, revealing distinct roles of dieselgenerators and micro gas turbines in microgrids. Overall, this study offersin-depth insights and practical guidance for microgrid design and operation.

Comparative study of microgrid optimal scheduling under multi-optimization algorithm fusion