Title: Optimisation method for economic dispatch of wind power connected to microgrid considering carbon emission

Authors: Hui Li; Xin Wen; Zhengyang Peng; Jing Zhang; Shitao Chen

Addresses: Metrology Centre of Guangzhou Power Supply Bureau, Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong, China ' Metrology Centre of Guangzhou Power Supply Bureau, Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong, China ' Metrology Centre of Guangzhou Power Supply Bureau, Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong, China ' Metrology Centre of Guangzhou Power Supply Bureau, Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong, China ' Guangzhou Jineng Information Technology Co., Ltd., Guangzhou, Guangdong, China

Abstract: In order to improve the economic dispatching effect of distribution network, the optimisation method of economic dispatching of wind power connected to microgrid considering carbon emissions is studied. Firstly, taking the minimum operating cost and environmental cost of wind power connected to microgrid as the design goal, and fully considering equality constraints and inequality constraints, an economic scheduling optimisation model of wind power connected to microgrid is constructed. Then, the improved particle swarm optimisation algorithm is used to solve the economic scheduling optimisation model of wind power connected to microgrid, and the economic scheduling optimisation is realised. Finally, the practicability of the proposed method is proved by experiments. The experimental results show that this method has strong calculation ability and good iterative performance in model solving, and the application of the proposed method can get more ideal economic dispatching effect and has high application value.

Keywords: carbon emissions; wind power access; microgrid; economic dispatch optimisation; particle swarm optimisation; abandoned air volume.

DOI: 10.1504/IJGEI.2025.147243

International Journal of Global Energy Issues, 2025 Vol.47 No.4/5, pp.515 - 533

Received: 27 Sep 2023
Accepted: 07 Feb 2024
Published online: 14 Jul 2025 *

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