Microgrid Scheduling Based on BAS-APSO Considering Wind Power Output Characteristics - Yang, Cheng; Yi, Yang; Yang, Zhennan; Chen, Jinchang; Miao, Lu (Distributed Generation & Alternative Energy Journal, 2026)
With the improvement of economic and social development level, microgrids have also experienced rapid development, but their optimization scheduling still faces huge challenges. Therefore, research has explored the multi-objective scheduling of microgrids. Firstly, a multi-objective optimization scheduling model for microgrids was established. Then, the particle swarm optimization algorithm is enhanced by combining dynamic inertia weights and the Beetle antenna search algorithm. When solving the Rosenbrock and Griebank functions, the proposed method had a fast convergence speed, taking 0.368s and 0.845s respectively, and could obtain a Pareto solution set that satisfies the convergence conditions. Improved particle swarm optimization algorithm could solve for lower fee optimization scheduling results in three different objective functions. The algorithm demonstrates efficacy in the domain of microgrid scheduling optimization. The research results contribute to maintaining the efficient and stable operation of microgrids and reducing operating fees.