A multi-layer-multi-player game model in electricity market

被引:1
作者
Kafshian, Hajar [1 ]
Monfared, Mohammad Ali Saniee [2 ]
机构
[1] Alzahra Univ, Dept Ind Engn, Tehran, Iran
[2] Alzahra Univ, Fac Engn, Dept Ind Engn, Tehran, Iran
关键词
demand side management; game theory; microgrids; smart power grids; DEMAND RESPONSE AGGREGATORS; COMPETITION;
D O I
10.1049/gtd2.13125
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
Here, a novel tri-level energy market model aimed at addressing the challenges posed by demand side management (DSM) in the electricity distribution company (EDC) is introduced. DSM has emerged as a new strategy employed by EDCs to manage and control electricity demand by encouraging end-users to modify their electricity consumption patterns. This is achieved through the participation of demand response (DR) aggregators, which play a crucial role in assisting end-users with strategies and technologies to reduce their electricity consumption during peak hours. The proposed tri-level energy market model consists of four distinct players: EDC, microgrids, aggregators, customers. The interactions between these four actors are modelled within a tri-level game framework, where the EDC and aggregators act as leaders, and the micro-grids and customers are followers. This multi-level and multi-player game structure allows for a more realistic representation of the complexities involved in DSM programs within the energy market. To demonstrate the effectiveness of the proposed model, a real case study is utilized, showing that the new model better resembles real-life market conditions. The results illustrate how the tri-level energy market model can significantly reduce demand fluctuations during peak hours, leading to improved efficiency and effectiveness within DSM programs.
引用
收藏
页码:1494 / 1515
页数:22
相关论文
共 26 条
  • [1] A Bayesian game theoretic based bidding strategy for demand response aggregators in electricity markets
    Abapour, Saeed
    Mohammadi-Ivatloo, Behnam
    Hagh, Mehrdad Tarafdar
    [J]. SUSTAINABLE CITIES AND SOCIETY, 2020, 54
  • [2] Robust bidding strategy for demand response aggregators in electricity market based on game theory
    Abapour, Saeed
    Mohammadi-Ivatloo, Behnam
    Hagh, Mehrdad Tarafdar
    [J]. JOURNAL OF CLEANER PRODUCTION, 2020, 243 (243)
  • [3] A trilevel model for best response in energy demand-side management
    Aussel, Didier
    Brotcorne, Luce
    Lepaul, Sebastien
    von Niederhausern, Leonard
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2020, 281 (02) : 299 - 315
  • [4] Bard J. F, 1998, Practical Bilevel Optimization: Algorithms and Applications
  • [5] BARD JF, 1998, NONCON OPTIM ITS APP, V30, P3
  • [6] On the Interaction Between Aggregators, Electricity Markets and Residential Demand Response Providers
    Bruninx, Kenneth
    Pandzic, Hrvoje
    Le Cadre, Helene
    Delarue, Erik
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2020, 35 (02) : 840 - 853
  • [7] Power Control in AC Isolated Microgrids With Renewable Energy Sources and Energy Storage Systems
    de Matos, Jose G.
    Silva, Felipe S. F. E.
    Ribeiro, Luiz A. de S.
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2015, 62 (06) : 3490 - 3498
  • [8] Dempe S., 2015, BILEVEL PROGRAMMING, V10, P973
  • [9] Dempe S, 2002, Foundations of Bilevel Programming
  • [10] Multi-process production scheduling with variable renewable integration and demand response
    Duarte, Jose Luis Ruiz
    Fan, Neng
    Jin, Tongdan
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2020, 281 (01) : 186 - 200