Introducing a Fuzzy Cognitive Map for Modeling Power Market Auction Behavior

被引:0
|
作者
Case, Denise M. [1 ]
Stylios, Chrysostomos D. [2 ]
机构
[1] Northwest Missouri State Univ, Sch Comp Sci & Informat Syst, Intelligent Syst Lab, 800 Univ Dr, Maryville, MO 64468 USA
[2] Technol Educ Inst Epirus, Knowledge & Intelligent Comp Lab, Dept Comp Engn, Arta, Greece
关键词
Power market; modeling; Fuzzy Cognitive Maps; decision support; soft computing; cyberphysical systems; distributed generation; SYSTEM;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The power market is becoming more complex as independent small producers are entering it but their energy offerings are often based on alternative sources which may be dependent on transient weather conditions. Power market auction behavior is a typical large-scale system characterized by huge amounts of data and information that have to be taken into consideration to make decisions. Fuzzy Cognitive Maps (FCM) offer a method for using the knowledge and experience of domain experts to describe the behavior of a complex system. This paper discusses FCM representation and development, and describes the use of FCM to develop a behavioral model of the system. This paper then presents the soft computing approach of FCM for modeling complex power market behavior. The resulting FCM models a variety of factors that affect individual participant behaviors during power auctions and provides an abstract conceptual model of the interacting entities for a specific case problem.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] Bidding Strategy in Continuous Double Auction Market Based on Fuzzy Cognitive Map
    Luan Haijun
    Dong Hongbin
    Qi Feng
    Yue Pan
    2016 IEEE INTERNATIONAL CONFERENCE ON REAL-TIME COMPUTING AND ROBOTICS (IEEE RCAR), 2016, : 144 - 149
  • [2] Introducing interval analysis in Fuzzy Cognitive Map framework
    Papageorgiou, Elpiniki
    nos Stylios, Chrysosto
    Groumpos, Peter
    ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2006, 3955 : 571 - 575
  • [3] Fuzzy cognitive state map VS Markovian modeling of user's web behavior
    Meghabghab, G
    2001 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5: E-SYSTEMS AND E-MAN FOR CYBERNETICS IN CYBERSPACE, 2002, : 1167 - 1172
  • [4] Introducing Fuzzy Cognitive Map for predicting Engine?s Health Status
    Tirovolas, Marios
    Stylios, Chrysostomos
    IFAC PAPERSONLINE, 2022, 55 (02): : 246 - 251
  • [5] The equivalence of Cognitive Map, Fuzzy Cognitive Map and Multi Value Fuzzy Cognitive Map
    Miao, Yuan
    Tao, XueHong
    Shen, ZhiQi
    Liu, ZhiQiang
    Miao, ChunYan
    2006 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-5, 2006, : 1872 - +
  • [6] Fuzzy cognitive map and people's web behavior
    Meghabghab, G
    PROCEEDINGS OF THE 7TH JOINT CONFERENCE ON INFORMATION SCIENCES, 2003, : 253 - 258
  • [7] A Novel Approach to Fuzzy Cognitive Map Based on Hesitant Fuzzy Sets for Modeling Risk Impact on Electric Power System
    Liu, Xiaodi
    Wang, Zengwen
    Zhang, Shitao
    Liu, Jiashu
    INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2019, 12 (02) : 842 - 854
  • [8] A Novel Approach to Fuzzy Cognitive Map Based on Hesitant Fuzzy Sets for Modeling Risk Impact on Electric Power System
    Xiaodi Liu
    Zengwen Wang
    Shitao Zhang
    Jiashu Liu
    International Journal of Computational Intelligence Systems, 2019, 12 : 842 - 854
  • [9] Modeling renewable energy usage with hesitant Fuzzy cognitive map
    Coban, Veysel
    Onar, Sezi Cevik
    COMPLEX & INTELLIGENT SYSTEMS, 2017, 3 (03) : 155 - 166
  • [10] A Fuzzy Cognitive Map Approach for Modeling CPFR Supporting Factors
    Buyukozkan, G.
    Vardaloglu, Z.
    Feyzioglu, O.
    WORLD CONGRESS ON ENGINEERING 2009, VOLS I AND II, 2009, : 566 - 571