LAPSE:2020.0035
Published Article
LAPSE:2020.0035
Game Analysis of Wind Storage Joint Ventures Participation in Power Market Based on a Double-Layer Stochastic Optimization Model
Bin Ma, Shiping Geng, Caixia Tan, Dongxiao Niu, Zhijin He
January 6, 2020
The volatility of a new energy output leads to bidding bias when participating in the power market competition. A pumped storage power station is an ideal method of stabilizing new energy volatility. Therefore, wind power suppliers and pumped storage power stations first form wind storage joint ventures to participate in power market competition. At the same time, middlemen are introduced, constructing an upper-level game model (considering power producers and wind storage joint ventures) that forms equilibrium results of bidding competition in the wholesale and power distribution markets. Based on the equilibrium result of the upper-level model, a lower model is constructed to distribute the profits from wind storage joint ventures. The profits of each wind storage joint venture, wind power supplier, and pumped storage power station are obtained by the Nash negotiation and the Shapely value method. Finally, a case study is conducted. The results show that the wind storage joint ventures can improve the economics of the system. Further, the middlemen can smooth the rapid fluctuation of power price in the distribution and wholesale market, maintaining a smooth and efficient operation of the electricity market. These findings provide information for the design of an electricity market competition mechanism and the promotion of new energy power generation.
Keywords
Nash negotiation, power market, Shapely value, wind storage joint ventures
Suggested Citation
Ma B, Geng S, Tan C, Niu D, He Z. Game Analysis of Wind Storage Joint Ventures Participation in Power Market Based on a Double-Layer Stochastic Optimization Model. (2020). LAPSE:2020.0035
Author Affiliations
Ma B: North China Electric Power University, Beijing 102206, China; North China Power Engineering Co. Ltd. of China Power Engineering Consulting Group, Beijing 100120, China [ORCID]
Geng S: North China Electric Power University, Beijing 102206, China
Tan C: North China Electric Power University, Beijing 102206, China
Niu D: North China Electric Power University, Beijing 102206, China
He Z: North China Electric Power University, Beijing 102206, China
Journal Name
Processes
Volume
7
Issue
12
Article Number
E896
Year
2019
Publication Date
2019-12-02
Published Version
ISSN
2227-9717
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PII: pr7120896, Publication Type: Journal Article
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LAPSE:2020.0035
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doi:10.3390/pr7120896
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Jan 6, 2020
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Calvin Tsay
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