A Review of Power System Dynamic State Estimation Techniques

被引:0
|
作者
Shivakumar, N. R. [1 ]
Jain, Amit [1 ]
机构
[1] IIIT, Power Syst Res Ctr, Hyderabad, Andhra Pradesh, India
关键词
dynamic state estimation; kalman filter; real time monitoring; square root filter; static state estimation;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
State estimation is a key Energy Management System (EMS) function, responsible for estimating the state of the power system. Power system is a quasi-static system and hence changes slowly with time. Since state estimation is computationally expensive, it is not easy to execute it repetitively at short intervals to achieve real time monitoring of such a changing system. Dynamic State Estimation (DSE) techniques model the time varying nature of the system, which allows it to predict the state vector in advance. This proves to be a major advantage for the operator in performing security analysis and other control center functions. Various techniques for dynamic state estimation are available in the literature. This paper presents a bird's eye view on different methodologies and developments in DSE, based on our comprehensive survey of the available literature.
引用
收藏
页码:502 / 507
页数:6
相关论文
共 50 条
  • [31] Roles of Dynamic State Estimation in Power System Modeling, Monitoring and Operation
    Zhao, Junbo
    Netto, Marcos
    Huang, Zhenyu
    Yu, Samson Shenglong
    Gomez-Exposito, Antonio
    Wang, Shaobu
    Kamwa, Innocent
    Akhlaghi, Shahrokh
    Mili, Lamine
    Terzija, Vladimir
    Meliopoulos, A. P. Sakis
    Pal, Bikash
    Singh, Abhinav Kumar
    Abur, Ali
    Bi, Tianshu
    Rouhani, Alireza
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2021, 36 (03) : 2462 - 2472
  • [32] Fusion of PMU and SCADA Data for Dynamic State Estimation of Power System
    Ghosal, Malini
    Rao, Vittal
    2015 NORTH AMERICAN POWER SYMPOSIUM (NAPS), 2015,
  • [33] A Data-driven Approach to Power System Dynamic State Estimation
    Kumari, Deepika
    Bhattacharyya, S. P.
    2017 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEM APPLICATION TO POWER SYSTEMS (ISAP), 2017,
  • [34] Power System Dynamic State Estimation Based on a New Particle Filter
    Chen Huanyuan
    Liu Xindong
    She Caiqi
    Yao Cheng
    2011 2ND INTERNATIONAL CONFERENCE ON CHALLENGES IN ENVIRONMENTAL SCIENCE AND COMPUTER ENGINEERING (CESCE 2011), VOL 11, PT B, 2011, 11 : 655 - 661
  • [35] POWER-SYSTEM DYNAMIC STATE ESTIMATION ON BASIS OF NOMINAL PATH
    YOKOYAMA, R
    KISHIDA, T
    TAMURA, Y
    ELECTRICAL ENGINEERING IN JAPAN, 1974, 94 (03) : 80 - 87
  • [36] Power system dynamic state estimation with mixed measurements based on UKF
    Li, Dalu
    Li, Rui
    Sun, Yuanzhang
    Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2010, 34 (17): : 17 - 21
  • [37] Synchrophasor Measurements based Power System Distributed Dynamic State Estimation
    Bi, Tianshu
    Yuan, Dongze
    Chen, Liang
    Liu, Hao
    Yang, Qixun
    2015 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, 2015,
  • [38] Dynamic harmonic state estimation of a power system based on adaptive SRUKF
    Zhang M.
    Xu S.
    Lu D.
    Xia R.
    He
    Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control, 2023, 51 (02): : 102 - 111
  • [39] DYNAMIC STATE ESTIMATION IN POWER SYSTEMS
    MILLER, WL
    LEWIS, JB
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1971, AC16 (06) : 841 - +
  • [40] POWER SYSTEM STATE ESTIMATION
    SMITH, OJM
    IEEE TRANSACTIONS ON POWER APPARATUS AND SYSTEMS, 1970, PA89 (03): : 363 - +