A two-level refinement method for operational rules in smart control centers

被引:0
|
作者
Wang, Kang [1 ]
Sun, Hongbin [1 ]
Jiang, Weiyong [1 ]
Zhang, Boming [1 ]
机构
[1] State Key Lab. of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
关键词
Heuristic methods - Electric power transmission networks - Knowledge representation - Decision making - Electric power transmission;
D O I
暂无
中图分类号
学科分类号
摘要
In order to improve the intelligence of power system dispatching, a two-level refinement method for operational rules in smart control centers for transmission corridors is proposed. The method includes three stages: data generation stage, in which a theme definition method, involving candidate attribute set, sample space and simulation mode, is proposed; feature selection stage, in which a heuristic regress feature selection (HRFS) method, which is suitable for continuous attributes, is introduced; rule extraction stage, in which a two-level refinement method based on linear regression tree is proposed for knowledge representation. Operational rules are built in a 4-generator 2-area test system and a realistic provincial power system using the method proposed in this paper. As the important features are selected and section rules are generated in operation sub-space, the new fine operational rules are of higher accuracy and better applicability. With the support of the operational rules, the transmission corridor capacity can be utilized more efficiently, and the control sensitivity contained in the rules is more helpful for decision-making of control strategy. © 2010 State Grid Electric Power Research Institute Press.
引用
收藏
页码:45 / 49
相关论文
共 50 条
  • [1] Two-Level Hierarchical Hybrid Control for Smart Power System
    Dou, C. X.
    Duan, Z. S.
    Liu, B.
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2013, 10 (04) : 1037 - 1049
  • [2] LEARNING SPARSE TWO-LEVEL BOOLEAN RULES
    Su, Guolong
    Wei, Dennis
    Varshney, Kush R.
    Malioutov, Dmitry M.
    2016 IEEE 26TH INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP), 2016,
  • [3] Compiling generalized two-level rules and grammars
    Yli-Jyra, Anssi
    Koskenniemi, Kimmo
    ADVANCES IN NATURAL LANGUAGE PROCESSING, PROCEEDINGS, 2006, 4139 : 174 - 185
  • [4] Smart substation advanced application software adapted for two-level distributed smart dispatch and control
    Sun, Hongbin
    Mu, Jianan
    Sheng, Tongtian
    Li, Qingxin
    Wang, Jing
    Wang, Bin
    Wang, Xuran
    Ji, Guoqiang
    Wu, Wenchuan
    Guo, Qinglai
    Li, Yalou
    Wang, Dexing
    Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2015, 39 (01): : 233 - 240
  • [5] Refinement of Fuzzy Diagnosis in Decentralized Two-Level Diagnostic Structure
    Syfert, M.
    Bartys, M.
    Koscielny, J. M.
    IFAC PAPERSONLINE, 2018, 51 (24): : 160 - 167
  • [6] Smart Charging Control for Electrical Vehicles Based on Two-level Charge Management System
    Yuan, Zengquan
    Xu, Haiping
    Han, Huachun
    Zhao, Yingjie
    2012 15TH INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS 2012), 2012,
  • [7] Quantum control of two-level systems
    Rosas-Ortiz, O
    PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON SQUEEZED STATES AND UNCERTAINTY RELATIONS, 2003, : 360 - 365
  • [8] Two-level optimization method for optimal control of a class of hybrid systems
    Zhang, JH
    Zhao, LK
    Kwon, WH
    2001 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS I-IV, PROCEEDINGS, 2001, : 1845 - 1850
  • [9] A Two-Level Distillation Design Method
    Amale, Amit
    Lucia, Angelo
    AICHE JOURNAL, 2008, 54 (11) : 2888 - 2903
  • [10] A two-level method for clustering DTDs
    Qian, WN
    Zhang, L
    Liang, YQ
    Qian, HL
    Jin, W
    WEB-AGE INFORMATION MANAGEMENT, PROCEEDINGS, 2000, 1846 : 41 - 52