Probabilistic small signal analysis using Monte Carlo simulation

被引:0
|
作者
Xu, Z [1 ]
Dong, ZY [1 ]
Zhang, P [1 ]
机构
[1] Univ Queensland, Sch Informat Technol & Elect Engn, Brisbane, Qld 4072, Australia
关键词
small signal stability; probabilistic methods; Monte Carlo simulation; eigenvalue; eigenvector; participation factor;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper presents a Monte Carlo approach for probabilistic small signal stability (PSSS) analysis in electric power systems with uncertainties. The uncertainties considered include both generation and demand in power systems, though others, such as parameter changes of network components, can be added as well. Probabilistic models of these uncertainties are constructed considering their characteristics. Subsequently, probabilistic small signal stability assessment of the power system is carried out based on eigenvalue analysis via Monte Carlo Simulation. The proposed method is tested by analysing the eigenvalues of two benchmark systems, where stable, unstable and oscillation modes are identified in the probabilistic context. In addition, local and inter-area modes of electro-mechanical oscillation are classified. Relevant discussion of stability enhancement using the proposed approach has been presented as well. The proposed method aims at providing a comprehensive characterization of system stability which can be very helpful in applications, such as system operation and expansion planning in the deregulation with many uncertainties.
引用
收藏
页码:1658 / 1664
页数:7
相关论文
共 50 条
  • [31] Efficient Monte Carlo Simulation of parameter sensitivity in probabilistic slope stability analysis
    Wang, Yu
    Cao, Zijun
    Au, Siu-Kui
    COMPUTERS AND GEOTECHNICS, 2010, 37 (7-8) : 1015 - 1022
  • [32] Probabilistic limit state analysis of framed structures. the Monte Carlo simulation
    Skowronek, M
    8TH INTERNATIONAL CONFERENCE ON MODERN BUILDING MATERIALS, STRUCTURES AND TECHNIQUES, 2004, : 905 - 908
  • [33] MODIFIED MONTE-CARLO SIMULATION FOR PROBABILISTIC SCHEDULING
    DIAZ, CF
    HADIPRIONO, FC
    CIVIL ENGINEERING SYSTEMS, 1992, 9 (04): : 337 - 347
  • [34] Probabilistic analysis of bridge networks based on system reliability and Monte Carlo simulation
    Akgül, F
    Frangopol, DM
    APPLICATIONS OF STATISTICS AND PROBABILITY IN CIVIL ENGINEERING, VOLS 1 AND 2, 2003, : 1633 - 1637
  • [35] Monte Carlo analysis of the small-signal response of charge carriers
    Kosina, H
    Nedjalkov, M
    Selberherr, S
    LARGE-SCALE SCIENTIFIC COMPUTING, 2001, 2179 : 175 - 182
  • [36] Soccer championship analysis using Monte Carlo simulation
    Silva, CF
    Garcia, ES
    Saliby, E
    PROCEEDINGS OF THE 2002 WINTER SIMULATION CONFERENCE, VOLS 1 AND 2, 2002, : 2011 - 2016
  • [37] ANALYSIS OF SPECT USING MONTE-CARLO SIMULATION
    BECK, JW
    JASZCZAK, RJ
    STARMER, CF
    PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS, 1982, 372 : 32 - 38
  • [38] ANALYSIS OF ULTRASONIC MACHINING USING MONTE CARLO SIMULATION
    Sahay, Chittaranjan
    Ghosh, Suhash
    Kammila, Hari Kiran
    PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION 2011, VOL 3, 2012, : 881 - 889
  • [39] Process capability analysis using Monte Carlo simulation
    Abdolshah, Mohammad
    Ismail, Md. Yusof B.
    Yusuff, Rosnah Mohd.
    Hong, Tang Sai
    2009 INTERNATIONAL CONFERENCE ON INFORMATION MANAGEMENT AND ENGINEERING, PROCEEDINGS, 2009, : 335 - +
  • [40] Using Monte Carlo simulation for pavement cost analysis
    Herbold, Keith D.
    Public Roads, 2000, 64 (03) : 2 - 6