Article Details

Abstract

In the context of increasing global attention to environmental issues, microgrids containing renewable energy are favored as clean and sustainable energy solutions. In order to effectively utilize renewable energy and achieve a balance between economy and environmental protection, a multi-objective optimization model is proposed. Firstly, the linear weighting method is used to balance the economic and environmental objective functions of the microgrid system. Then, the Simulated Annealing Particle Swarm Optimization algorithm is introduced to solve the multi-objective optimization model, to achieve the goal of optimizing the economic and environmental objectives. The simulation results show that introducing Simulated Annealing Particle Swarm Optimization algorithm can effectively improve system performance when solving multi-objective optimization problems in microgrids, and makes the operation state of microgrids more economically efficient and environmentally friendly, thereby promoting the sustainable development of renewable energy microgrids.

Keywords

microgrid; Simulated Annealing Particle Swarm Optimization algorithm; optimal scheduling; multi-objective optimization

References

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Funding

Higher Education Science Research Project of Guizhou Provincial Department of Education (Qianjiaoji [2022] No. 383)

About the authors

Mei Yu (1997-), female, Han ethnicity, from Duyun, Guizhou, lecturer, master's degree, research direction: smart grid.