{"title":"IGDT-based demand response strategy for an integrated energy system considering its interactions with multi-energy markets","authors":"Biao Wu, Shaohua Zhang, Chenxin Yuan, Xian Wang, Fei Wang, Shengqi Zhang","doi":"10.1016/j.ijepes.2025.110516","DOIUrl":null,"url":null,"abstract":"<div><div>An integrated energy system (IES) can achieve multi-energy complementarity via its integrated demand response (IDR) program. With the continuous development of IES and the advancement of its marketization, investigating the IDR strategy of IES when it acts as a price maker in multi-energy markets holds significant importance. In this paper, we propose a bi-level model to determine the IDR strategy of an IES by considering its interactions with multi-energy markets. The upper-level formulates the IES’s IDR decision-making in response to the electricity and natural gas prices, including electricity purchases from the electricity market (EM), natural gas purchases from the natural gas market (NGM), electricity and heat consumption. The lower-level describes the games of supply function bidding among the power generators (PGs) in EM and the natural gas companies (NGCs) in NGM. Specifically, using ordinal potential game (OPG) theory, we construct an ordinal potential function (OPF) for the OPG model of multi-energy markets. This enables us to find the Nash equilibrium (NE) of the games in EM and NGM through the multi-energy markets’ OPF. The information gap decision theory (IGDT) is employed to address the severe uncertainty of wind power. Furthermore, the existence and uniqueness of the solution for the bi-level model are theoretically proven. Based on this, we develop a distributed algorithm to handle the information asymmetry. Simulation results demonstrate the effectiveness of the proposed model and algorithm, revealing that when IES acts as a price maker in multi-energy markets, it can mitigate the market power of both PGs and NGCs.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"166 ","pages":"Article 110516"},"PeriodicalIF":5.0000,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Electrical Power & Energy Systems","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0142061525000675","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
An integrated energy system (IES) can achieve multi-energy complementarity via its integrated demand response (IDR) program. With the continuous development of IES and the advancement of its marketization, investigating the IDR strategy of IES when it acts as a price maker in multi-energy markets holds significant importance. In this paper, we propose a bi-level model to determine the IDR strategy of an IES by considering its interactions with multi-energy markets. The upper-level formulates the IES’s IDR decision-making in response to the electricity and natural gas prices, including electricity purchases from the electricity market (EM), natural gas purchases from the natural gas market (NGM), electricity and heat consumption. The lower-level describes the games of supply function bidding among the power generators (PGs) in EM and the natural gas companies (NGCs) in NGM. Specifically, using ordinal potential game (OPG) theory, we construct an ordinal potential function (OPF) for the OPG model of multi-energy markets. This enables us to find the Nash equilibrium (NE) of the games in EM and NGM through the multi-energy markets’ OPF. The information gap decision theory (IGDT) is employed to address the severe uncertainty of wind power. Furthermore, the existence and uniqueness of the solution for the bi-level model are theoretically proven. Based on this, we develop a distributed algorithm to handle the information asymmetry. Simulation results demonstrate the effectiveness of the proposed model and algorithm, revealing that when IES acts as a price maker in multi-energy markets, it can mitigate the market power of both PGs and NGCs.
期刊介绍:
The journal covers theoretical developments in electrical power and energy systems and their applications. The coverage embraces: generation and network planning; reliability; long and short term operation; expert systems; neural networks; object oriented systems; system control centres; database and information systems; stock and parameter estimation; system security and adequacy; network theory, modelling and computation; small and large system dynamics; dynamic model identification; on-line control including load and switching control; protection; distribution systems; energy economics; impact of non-conventional systems; and man-machine interfaces.
As well as original research papers, the journal publishes short contributions, book reviews and conference reports. All papers are peer-reviewed by at least two referees.