Research on the bi-layer low carbon optimization strategy of integrated energy system based on Stackelberg master slave game

Wu, L; Wang, C; Chen, W; Pei, T

Research on the bi-layer low carbon optimization strategy of integrated energy system based on Stackelberg master slave game

Wu, L Wang, C Chen, W Pei, T

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Global Energy Interconnection, 2023, 6, (4), pp. 389-402
Issue Date:: 2023-08-01

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Field	Value	Language
dc.contributor.author	Wu, L
dc.contributor.author	Wang, C
dc.contributor.author	Chen, W
dc.contributor.author	Pei, T
dc.date.accessioned	2024-05-27T04:05:13Z
dc.date.available	2024-05-27T04:05:13Z
dc.date.issued	2023-08-01
dc.identifier.citation	Global Energy Interconnection, 2023, 6, (4), pp. 389-402
dc.identifier.issn	2096-5117
dc.identifier.issn	2590-0358
dc.identifier.uri	http://hdl.handle.net/10453/179226
dc.description.abstract	With increasing reforms related to integrated energy systems (IESs), each energy subsystem, as a participant based on bounded rationality, significantly influences the optimal scheduling of the entire IES through mutual learning and imitation. A reasonable multiagent joint operation strategy can help this system meet its low-carbon objectives. This paper proposes a bilayer low-carbon optimal operational strategy for an IES based on the Stackelberg master-slave game and multiagent joint operation. The studied IES includes cogeneration, power-to-gas, and carbon capture systems. Based on the Stackelberg master-slave game theory, sellers are used as leaders in the upper layer to set the prices of electricity and heat, while energy producers, energy storage providers, and load aggregators are used as followers in the lower layer to adjust the operational strategy of the system. An IES bilayer optimization model based on the Stackelberg master-slave game was developed. Finally, the Karush-Kuhn-Tucker (KKT) condition and linear relaxation technology are used to convert the bilayer game model to a single layer. CPLEX, which is a mathematical program solver, is used to solve the equilibrium problem and the carbon emission trading cost of the system when the benefits of each subject reach maximum and to analyze the impact of different carbon emission trading prices and growth rates on the operational strategy of the system. As an experimental demonstration, we simulated an IES coupled with an IEEE 39-node electrical grid system, a six-node heat network system, and a six-node gas network system. The simulation results confirm the effectiveness and feasibility of the proposed model.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Global Energy Interconnection
dc.relation.isbasedon	10.1016/j.gloei.2023.08.002
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	4008 Electrical engineering
dc.title	Research on the bi-layer low carbon optimization strategy of integrated energy system based on Stackelberg master slave game
dc.type	Journal Article
utslib.citation.volume	6
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	open_access	*
dc.date.updated	2024-05-27T04:05:12Z
pubs.issue	4
pubs.publication-status	Published
pubs.volume	6
utslib.citation.issue	4

Abstract:

With increasing reforms related to integrated energy systems (IESs), each energy subsystem, as a participant based on bounded rationality, significantly influences the optimal scheduling of the entire IES through mutual learning and imitation. A reasonable multiagent joint operation strategy can help this system meet its low-carbon objectives. This paper proposes a bilayer low-carbon optimal operational strategy for an IES based on the Stackelberg master-slave game and multiagent joint operation. The studied IES includes cogeneration, power-to-gas, and carbon capture systems. Based on the Stackelberg master-slave game theory, sellers are used as leaders in the upper layer to set the prices of electricity and heat, while energy producers, energy storage providers, and load aggregators are used as followers in the lower layer to adjust the operational strategy of the system. An IES bilayer optimization model based on the Stackelberg master-slave game was developed. Finally, the Karush-Kuhn-Tucker (KKT) condition and linear relaxation technology are used to convert the bilayer game model to a single layer. CPLEX, which is a mathematical program solver, is used to solve the equilibrium problem and the carbon emission trading cost of the system when the benefits of each subject reach maximum and to analyze the impact of different carbon emission trading prices and growth rates on the operational strategy of the system. As an experimental demonstration, we simulated an IES coupled with an IEEE 39-node electrical grid system, a six-node heat network system, and a six-node gas network system. The simulation results confirm the effectiveness and feasibility of the proposed model.

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http://hdl.handle.net/10453/179226