Determination of transmission reliability margin using probabilistic load flow

被引:0
|
作者
Lee, JK [1 ]
Shin, DJ [1 ]
Lee, HS [1 ]
Jung, HS [1 ]
Kim, JO [1 ]
机构
[1] Hanyang Univ, Dept Elect Engn, Seoul 133791, South Korea
来源
PROCEEDINGS OF THE FOURTH IASTED INTERNATIONAL CONFERENCE ON POWER AND ENERGY SYSTEMS | 2004年
关键词
ATC; Monte-Carlo simulation; PLF; TRM;
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
According to NERC definition, Available Transfer Capability (ATC) is a measure of the transfer capability remaining in the physical transmission network for the future commercial activity. To calculate ATC, accurate and defensible TTC, CBM and TRM should be calculated in advance. This paper proposes a method to quantify time varying Transmission Reliability Margin (TRM) based on probabilistic load flow (PLF) using the method of moments. The uncertainties of power system and market, such as generation output, bus voltages, line outages, line flow and cancellation of power delivery contracts are considered as time varying complex random variables (CRV) in the PLF process. As a result of PLF analysis, Probability Density Function (PDF) of line flow and bus voltage at the transfer interface are acquired, and TRM with the desired probabilistic margin is calculated based on these PDFs. One distinguishing feature of the proposed method is that the TTC and TRM can be computed as a function of a specified probability margin. Suggested TRM quantification method is compared with the results with Monte-Carlo simulation and verified using 24 bus MRTS. The proposed method based on PLF shows efficiency and flexibility for the quantification of TRM.
引用
收藏
页码:350 / 355
页数:6
相关论文
共 50 条
  • [21] Probabilistic Reliability Planning at British Columbia Transmission Corporation: Method and Project Case
    Li, W.
    Choudhury, P.
    Gurney, J. H.
    2008 10TH INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS, 2008, : 562 - 568
  • [22] Probabilistic modeling of aquifer heterogeneity using reliability methods
    Hamed, MM
    Bedient, PB
    Dawson, CN
    ADVANCES IN WATER RESOURCES, 1996, 19 (05) : 277 - 295
  • [23] Probabilistic load flow solution considering reactive power and voltage control
    Nimpitiwan, N.
    Chaiyabut, N.
    2007 CONFERENCE PROCEEDINGS IPEC, VOLS 1-3, 2007, : 80 - 85
  • [24] Combined cumulants and Laplace transform method for probabilistic load flow analysis
    Kenari, Meghdad Tourandaz
    Sepasian, Mohammad Sadegh
    Nazar, Mehrdad Setayesh
    Mohammadpour, Hossein Ali
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2017, 11 (14) : 3548 - 3556
  • [25] Probabilistic load flow calculation based on sparse polynomial chaos expansion
    Sun, Xin
    Tu, Qingrui
    Chen, Jinfu
    Zhang, Chengwen
    Duan, Xianzhong
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2018, 12 (11) : 2735 - 2744
  • [26] Probabilistic Load Flow Analysis in Distribution Networks with Distributed Solar Generation
    Warren, Julian J.
    Negnevitsky, Michael
    Thanh Nguyen
    2016 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING (PESGM), 2016,
  • [27] Probabilistic load flow evaluation considering correlated input random variables
    Xu, Xiaoyuan
    Yan, Zheng
    INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS, 2016, 26 (03): : 555 - 572
  • [28] Probabilistic load flow with versatile non-Gaussian power injections
    Carmona-Delgado, Cristina
    Romero-Ramos, Esther
    Riquelme-Santos, Jesus
    ELECTRIC POWER SYSTEMS RESEARCH, 2015, 119 : 266 - 277
  • [29] Impact of the line resistance statistical distribution on a Probabilistic Load Flow computation
    Codjo, Egnonnumi Lorraine
    Vallee, Francois
    Francois, Bruno
    2020 6TH IEEE INTERNATIONAL ENERGY CONFERENCE (ENERGYCON), 2020, : 637 - 642
  • [30] A Markov Chain Based Method for Probabilistic Load Flow with Wind Power
    Zhu, Jin-Zhou
    Zhao, Teng
    Zhang, Yan
    2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, 2017,