[Oral Presentation]Optimization strategy for multi-microgrid power sharing operation considering low-carbon characteristics

Optimization strategy for multi-microgrid power sharing operation considering low-carbon characteristics
ID:52 Submission ID:93 View Protection:ATTENDEE Updated Time:2023-11-20 13:45:37 Hits:135 Oral Presentation

Start Time:Pending (Asia/Shanghai)

Duration:Pending

Session:[No Session] » [No Session Block]

Presentation File

Tips: The file permissions under this presentation are only for participants. You have not logged in yet and cannot view it temporarily.

Abstract
Improving the utilization of renewable energy and transforming traditional microgrids into low-carbon ones are important means to achieve energy and power carbon peak and carbon neutrality goals. In this paper, we first construct a microgrid model that includes electric, thermal, and gas energy coordination, and introduce a carbon capture system into the cogeneration unit model to reduce carbon emissions. Then, a multi-microgrid power-sharing operation model is constructed according to the Nash negotiation principle, and thus discretized as the coalition benefit optimization sub-problem and the benefit distribution sub-problem. To safeguard each subject's identity, we use the distributed direction manifold technique. In the revenue redistribution sub-problem, we construct an asymmetric energy mapping contribution function to achieve reasonable revenue redistribution. The results show that this approach is efficient in cutting carbon output during microgrid operation while reducing operating costs, and has the advantage of reducing carbon emissions.
Keywords
Carbon capture; Cooperative game; Low-carbon optimal operation; Multi-microgrid; Nash bargaining;
Speaker
Mingcheng Dai
graduate student Huazhong University Of Science And Technology

Submission Author
Mingcheng Dai Huazhong University Of Science And Technology
Lee Li 华中科技大学
Comment submit
Verification code Change another
All comments

Contact us

Southwest Jiaotong University

(SWJTU)

Add: No.999, Xi'an Road, Pidu

District, Chengdu City, Sichuan

Province,611756 China

Email: ciycee2023@163.com

 

Aconf Staff:Lu Wei

Tel:+86 18971567453
Email:luwei@chytey.com

WeChat public account: 

IEEE IAS SWJTU Student Branch