{"title":"Distributed robust cooperative optimization of multi-integrated energy systems based on variational inequality-driven non-cooperative game theory","authors":"Zongnan Zhang , Kudashev Sergey Fedorovich","doi":"10.1016/j.apenergy.2025.126696","DOIUrl":null,"url":null,"abstract":"<div><div>In integrated energy system (IES), multiple uncertainties exist regarding renewable energy output and electricity prices, while traditional electric hydrogen module model fail to accurately characterize the operational states of electrolyzer. Additionally, complex coupling and competitive interests among multi-integrated energy system (MIES) pose significant challenges for effective management. To address these challenges, this paper integrates non-cooperative game theory with distributionally robust optimization (DRO) to propose an efficient and robust operational strategy for MIES. Firstly, a DRO model for IES is established using Wasserstein distance, allowing for a refined modeling of the electric hydrogen module. Subsequently, a non-cooperative game equilibrium model based on variational inequalities (VI) is constructed to describe the interactions among MIES, leading to the development of a VI-driven equilibrium model for non-cooperative games in MIES under distributionally robust optimization. To achieve efficient equilibrium while safeguarding the privacy of each IES, an AOP-BL-ADMM algorithm is developed. Finally, the effectiveness of the proposed method is validated through case analysis.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"401 ","pages":"Article 126696"},"PeriodicalIF":11.0000,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0306261925014266","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
In integrated energy system (IES), multiple uncertainties exist regarding renewable energy output and electricity prices, while traditional electric hydrogen module model fail to accurately characterize the operational states of electrolyzer. Additionally, complex coupling and competitive interests among multi-integrated energy system (MIES) pose significant challenges for effective management. To address these challenges, this paper integrates non-cooperative game theory with distributionally robust optimization (DRO) to propose an efficient and robust operational strategy for MIES. Firstly, a DRO model for IES is established using Wasserstein distance, allowing for a refined modeling of the electric hydrogen module. Subsequently, a non-cooperative game equilibrium model based on variational inequalities (VI) is constructed to describe the interactions among MIES, leading to the development of a VI-driven equilibrium model for non-cooperative games in MIES under distributionally robust optimization. To achieve efficient equilibrium while safeguarding the privacy of each IES, an AOP-BL-ADMM algorithm is developed. Finally, the effectiveness of the proposed method is validated through case analysis.
期刊介绍:
Applied Energy serves as a platform for sharing innovations, research, development, and demonstrations in energy conversion, conservation, and sustainable energy systems. The journal covers topics such as optimal energy resource use, environmental pollutant mitigation, and energy process analysis. It welcomes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gap between research, development, and implementation. The journal addresses a wide spectrum of topics, including fossil and renewable energy technologies, energy economics, and environmental impacts. Applied Energy also explores modeling and forecasting, conservation strategies, and the social and economic implications of energy policies, including climate change mitigation. It is complemented by the open-access journal Advances in Applied Energy.