A Microgrid Management System Based on Metaheuristics Particle Swarm Optimization

Deng, Haotian; Jiang, Jing; Qian, Haiya; Sun, Hongjian

Abstract

Microgrid is playing an increasingly important role in making the utility grid more intelligent and efficient, since it can make better use of the renewable energy resources to simultaneously relieve the grid supply pressure and reduce carbon emissions. Innovations in electric technologies, information and communication technologies can facilitate better management of the power transmission and distribution in the microgrid. This paper proposes an optimization strategy, which considers distributed generations, photovoltaics and wind turbines, based on particle swarm optimization for the management of the microgrid. Simulation results demonstrate that with the optimal generation resources management and the effective use of demand side management in the microgrid, the proposed strategy can reduce electricity costs by 29.283% and 32.158% on weekdays and weekends, respectively.

Citation

Deng, H., Jiang, J., Qian, H., & Sun, H. (2022, October). A Microgrid Management System Based on Metaheuristics Particle Swarm Optimization. Presented at 6th International Conference on Smart Grid and Smart Cities (ICSGSC 2022), Chengdu, China

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 6th International Conference on Smart Grid and Smart Cities (ICSGSC 2022)
• Start Date: Oct 22, 2022
• End Date: Oct 24, 2022
• Acceptance Date: Jun 17, 2022
• Online Publication Date: Dec 1, 2022
• Publication Date: 2022
• Deposit Date: Jun 21, 2022
• Publicly Available Date: Oct 25, 2022
• Publisher: Institute of Electrical and Electronics Engineers
• Pages: 126-131
• DOI: https://doi.org/10.1109/icsgsc56353.2022.9963000
• Public URL: https://durham-repository.worktribe.com/output/1136661