Tri-layer low-carbon distributed optimization of integrated energy systems based on hybrid games under stochastic scenarios

被引:2
|
作者
Yue, Ziyi [1 ]
Liu, Huazhi [2 ]
Li, Yonggang [1 ,4 ]
Zhong, Yuyao [1 ]
Yao, Jiachen [3 ]
Li, Yuxuan [1 ]
机构
[1] North China Elect Power Univ, Dept Elect Engn, State Key Lab Alternate Elect Power Syst Renewable, Baoding, Peoples R China
[2] State Grid Tianjin Econ Res Inst, Tianjin, Peoples R China
[3] Jibei Chengde Power Supply Co, Chengde Cty Power Supply Branch Co, Jibei, Peoples R China
[4] North China Elect Power Univ, Dept Elect Engn, Yonghua North St 619, Baoding, Peoples R China
基金
中国国家自然科学基金;
关键词
distributed optimization; hybrid games; integrated energy system; low-carbon economic dispatch; stochastic scenarios; POWER;
D O I
10.1049/gtd2.13013
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The low-carbon development of integrated energy systems is achieved via the sharing of multiple energy interactions by park-level IES (PIES).However, coordinating profit distribution conflicts among complex interactive stakeholders in stochastic scenarios is challenging. Accordingly, this study proposes a novel tri-layer framework that aggregates different game mechanisms to investigate the interactions between PIESs and coupled energy markets. First, a linkage trading mechanism is proposed by integrating carbon emissions trading and green certificate trading, which establishes a coupled electricity-carbon-green certificate market. Consequently, a park aggregation operator acts as an intermediary between PIESs and the coupled market, setting upper-level purchase and sale prices to guide unit generation in each PIES using the Stackelberg game theory. Subsequently, the Nash game theory is applied to realize cooperative bargaining among PIESs for a fair revenue distribution. Further, the impact of uncertain environments is considered by utilizing stochastic scenario methods and the conditional value-at-risk theory. To protect the privacy of each participating agent while improving the convergence speed, a differential evolutionary method is combined with analysis target cascading to solve the framework. Finally, the proposed scheduling method is validated by utilizing a typical case to optimize conflicting PIES interests in multiple scenarios and realize decarbonisation. This study developed a trilayer framework based on hybrid games for implementation in power grids to improve energy-use efficiency, carbon-capture cycles, and resource sharing for maximum equitable revenue. Through the integration of different gaming methods and transaction mechanisms, a rational distribution of benefits among complexly interacting stakeholders can be achieved. It will aid in the improvement of energy management systems by effectively managing energy sources, storage mechanisms, and resource-sharing.image
引用
收藏
页码:5323 / 5339
页数:17
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