Application of Opportunistic Information-Gap Decision Theory on Demand Response Aggregator in the Day-Ahead Electricity Market

被引:3
|
作者
Vahid-Ghavidel, Morteza [1 ,2 ]
Catalao, Joao P. S. [1 ,2 ]
Shafie-khah, Miadreza [3 ]
Mohammadi-Ivatloo, Behnam [4 ]
Mahmoudi, Nadali [5 ]
机构
[1] FEUP, Porto, Portugal
[2] INESC TEC, Porto, Portugal
[3] Univ Vaasa, Technol & Innovat, Vaasa, Finland
[4] Univ Tabriz, Fac Elect & Comp Engn, Tabriz, Iran
[5] Ernst & Young, Brisbane, Qld, Australia
关键词
Demand response; information-gap decision theory; uncertainty; DR aggregator;
D O I
10.1109/isgteurope.2019.8905744
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The proposed model analyzes the profit of a demand response (DR) aggregator from trading DR in the day-ahead electricity market in a way that it tends to gain profit from the favorable deviations of the uncertain parameters. Two types of DR programs are implemented in this model, i.e., time-of-use and reward based DR program. The information-gap decision theory is being employed as a risk measure to address the uncertainties. Two uncertain parameters from both sides of the aggregator have been taken into account in this model, such as the participation rate of the consumers in reward-based DR program in the consumer-side of the aggregator and the day-ahead market prices in the wholesale-side of it. The program is simulated in GAMS software using the available commercial solver. Real data is considered to check the feasibility of the proposed program.
引用
收藏
页数:5
相关论文
共 50 条
  • [31] A NEW FRAMEWORK FOR DAY-AHEAD ELECTRICITY MARKET BASED ON INFORMATION TRANSPARENCY BEFORE MARKET SETTLEMENT
    Moazzen, H.
    Ameli, M. T.
    [J]. SAIEE AFRICA RESEARCH JOURNAL, 2015, 106 (01): : 21 - 27
  • [32] Master-Slave Game Based Optimal Pricing Strategy for Load Aggregator in Day-ahead Electricity Market
    Sun W.
    Liu X.
    Xiang W.
    Li H.
    [J]. Sun, Weiqing (sidswq@163.com), 1600, Automation of Electric Power Systems Press (45): : 159 - 167
  • [33] Optimal day-ahead scheduling for active distribution network based on improved information gap decision theory
    Ge, Xiaolin
    Zhu, Xiaohe
    Ju, Xing
    Fu, Yang
    Lo, Kwok Lun
    Mi, Yang
    [J]. IET RENEWABLE POWER GENERATION, 2021, 15 (05) : 952 - 963
  • [34] Integration Mechanisms for LQ Energy Day-ahead Market Based on Demand Response
    Okajima, Yusuke
    Murao, Toshiyuki
    Hirata, Kenji
    Uchida, Kenko
    [J]. 2014 IEEE CONFERENCE ON CONTROL APPLICATIONS (CCA), 2014, : 1 - 8
  • [35] Electric vehicle aggregator as demand dispatch resources: Exploring the impact of real-time market performance on day-ahead market
    Hu, Zhuo
    Wang, Tao
    Cao, Yuwei
    Yang, Qing
    [J]. ENERGY, 2024, 308
  • [36] Electricity Demand Elasticity, Mobility, and COVID-19 Contagion Nexus in the Italian Day-Ahead Electricity Market
    Bollino, Carlo Andrea
    D'Errico, Maria Chiara
    [J]. ENERGIES, 2022, 15 (20)
  • [37] Research on the impact of demand response programs in day ahead market on the oligarchs in the electricity market
    Gu, Huijie
    Hu, Rong
    He, Xiqi
    Zhou, Huafeng
    [J]. 2020 ASIA CONFERENCE ON GEOLOGICAL RESEARCH AND ENVIRONMENTAL TECHNOLOGY, 2021, 632
  • [38] Hourly Electricity Demand Response in the Stochastic Day-Ahead Scheduling of Coordinated Electricity and Natural Gas Networks
    Zhang, Xiaping
    Shahidehpour, Mohammad
    Alabdulwahab, Ahmed
    Abusorrah, Abdullah
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2016, 31 (01) : 592 - 601
  • [39] Maximal Daily Social Welfare through Demand Side Management in the Day-Ahead Electricity Market
    de la Nieta, Agustin A. Sanchez
    Gibescu, Madeleine
    [J]. 2018 15TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET (EEM), 2018,
  • [40] A Day-ahead and Day-in Decision Model Considering the Uncertainty of Multiple Kinds of Demand Response
    Sheng, Siqing
    Gu, Qing
    [J]. ENERGIES, 2019, 12 (09)