Application of Information-Gap Decision Theory to Risk-Constrained Self-Scheduling of GenCos

被引:152
|
作者
Mohammadi-Ivatloo, Behnam [1 ]
Zareipour, Hamidreza [2 ]
Amjady, Nima [3 ]
Ehsan, Mehdi [1 ]
机构
[1] Sharif Univ Technol, Dept Elect Engn, Ctr Excellence Power Syst Management & Control, Tehran, Iran
[2] Univ Calgary, Dept Elect & Comp Engn, Calgary, AB T2N 1N4, Canada
[3] Semnan Univ, Dept Elect Engn, Semnan 35195363, Iran
关键词
Electricity markets; information-gap decision theory (IGDT); price forecasts; self-scheduling; uncertainty; ELECTRICITY MARKET; UNCERTAINTY; PRODUCER; PROBABILITY; PROFIT; UNIT;
D O I
10.1109/TPWRS.2012.2212727
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
In a competitive electricity market, a generation company (GenCo) optimizes its operation schedules, referred to as self-scheduling, in order to maximize its profit. However, various sources of uncertainty, such as market price fluctuations or forced outage of generating units, may impact the GenCo's profit. In this paper, a non-probabilistic information-gap model is proposed to model the uncertainties in short-term scheduling of a GenCo. The self-scheduling problem is formulated for risk-neutral, risk-averse, and risk-seeker GenCos. Robustness of the decisions against low market prices are evaluated using a robustness model. Furthermore, windfall higher profit due to unpredicted higher market prices is modeled using an opportunity function. The proposed models are applied to a 54-unit thermal GenCo.
引用
收藏
页码:1093 / 1102
页数:10
相关论文
共 50 条
  • [31] Erratum to: Using Information-Gap Decision Theory for Water Resources Planning Under Severe Uncertainty
    Brett Korteling
    Suraje Dessai
    Zoran Kapelan
    [J]. Water Resources Management, 2013, 27 (4) : 1173 - 1174
  • [32] Evaluation of the Mini-Models Robustness to Data Uncertainty with the Application of the Information-Gap Theory
    Plucinski, Marcin
    [J]. ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, PT II, 2013, 7895 : 230 - 241
  • [33] Economic scheduling of a smart microgrid utilizing the benefits of plug-in electric vehicles contracts with a comprehensive model of information-gap decision theory
    Sriyakul, Thanaporn
    Jermsittiparsert, Kittisak
    [J]. JOURNAL OF ENERGY STORAGE, 2020, 32
  • [34] Application of the information-gap theory for evaluation of nearest neighbours method robustness to data uncertainty
    Plucinski, Marcin
    [J]. PRZEGLAD ELEKTROTECHNICZNY, 2012, 88 (10B): : 272 - 275
  • [35] Risk-Constrained Day-Ahead Scheduling for Concentrating Solar Power Plants With Demand Response Using Info-Gap Theory
    Zhao, Yuxuan
    Lin, Zhenzhi
    Wen, Fushuan
    Ding, Yi
    Hou, Jiaxuan
    Yang, Li
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2019, 15 (10) : 5475 - 5488
  • [36] Integrated Energy Microgrid Economic Dispatch Optimization Model Based on Information-Gap Decision Theory
    Fan, Xiaowei
    Chen, Yongtao
    Wang, Ruimiao
    Luo, Jiaxin
    Wang, Jingang
    Cao, Decheng
    [J]. ENERGIES, 2023, 16 (08)
  • [37] A Robust Model for Multiyear Distribution Network Reinforcement Planning Based on Information-Gap Decision Theory
    Ahmadigorji, Masoud
    Amjady, Nima
    Dehghan, Shahab
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2018, 33 (02) : 1339 - 1351
  • [38] Information-Gap Decision Theory for Robust Operation of Integrated Electricity and Natural Gas Transmission Networks
    Rostami, Ali Mohammad
    Ameli, Hossein
    Ameli, Mohammad Taghi
    Strbac, Goran
    [J]. 2020 INTERNATIONAL CONFERENCE ON SMART ENERGY SYSTEMS AND TECHNOLOGIES (SEST), 2020,
  • [39] Demand Response based Trading Framework in the Presence of Fuel Cells Using Information-Gap Decision Theory
    Vahid-Ghavidel, Morteza
    Javadi, Mohammad Sadegh
    Santos, Sergio F.
    Gough, Matthew
    Shafie-khah, Miadreza
    Catalao, Joao P. S.
    [J]. 2020 INTERNATIONAL CONFERENCE ON SMART ENERGY SYSTEMS AND TECHNOLOGIES (SEST), 2020,
  • [40] Improvement of regional market management considering reserve, information-gap decision theory, and emergency demand response program
    Hosseini, S. E.
    Najafi, M.
    Akhavein, A.
    [J]. SCIENTIA IRANICA, 2023, 30 (01) : 125 - 141