Game Theory-Based Bi-Level Capacity Allocation Strategy for Multi-Agent Combined Power Generation Systems

Zhiding Chen (), Yang Huang, Yi Dong and Ziyue Ni
Additional contact information
Zhiding Chen: College of Hydraulic and Environmental Engineering, China Three Gorges University, Yichang 443002, China
Yang Huang: College of Hydraulic and Environmental Engineering, China Three Gorges University, Yichang 443002, China
Yi Dong: Guohua (Hubei) New Energy Co., Ltd., Wuhan 430077, China
Ziyue Ni: College of Hydraulic and Environmental Engineering, China Three Gorges University, Yichang 443002, China

Energies, 2025, vol. 18, issue 20, 1-29

Abstract: The wind–solar–storage–thermal combined power generation system is one of the key measures for China’s energy structure transition, and rational capacity planning of each generation entity within the system is of critical importance. First, this paper addresses the uncertainty of wind and photovoltaic (PV) power outputs through scenario-based analysis. Considering the diversity of generation entities and their complex interest demands, a bi-level capacity optimization framework based on game theory is proposed. In the upper-level framework, a game-theoretic method is designed to analyze the multi-agent decision-making process, and the objective function of capacity allocation for multiple entities is established. In the lower-level framework, multi-objective optimization is performed on utility functions and node voltage deviations. The Nash equilibrium of the non-cooperative game and the Shapley value of the cooperative game are solved to study the differences in the capacity allocation, economic benefits, and power supply stability of the combined power generation system under different game modes. The case study results indicate that under the cooperative game mode, when the four generation entities form a coalition, the overall system achieves the highest supply stability, the lowest carbon emissions at 30,195.29 tons, and the highest renewable energy consumption rate at 53.93%. Moreover, both overall and individual economic and environmental performance are superior to those under the non-cooperative game mode. By investigating the capacity configuration and joint operation strategies of the combined generation system, this study effectively enhances the enthusiasm of each generation entity to participate in the energy market; reduces carbon emissions; and promotes the development of a more efficient, environmentally friendly, and economical power generation model.

Keywords: combined power generation system; game theory; uncertainty; bi-level capacity optimization; Nash equilibrium; Shapley (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/20/5338/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/20/5338/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:20:p:5338-:d:1768180

Access Statistics for this article

Energies is currently edited by Ms. Cassie Shen

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().