Probabilistic Load Flow Evaluation With Hybrid Latin Hypercube-Sampling and Cholesky Decomposition

被引：370
|
作者：
Yu, H. [1 ,2 ]
Chung, C. Y. [1 ]
Yong, K. P. [1 ,3 ]
Lee, H. W. [4 ]
Zhang, J. H. [2 ]
机构：
[1] Hong Kong Polytech Univ, Dept Elect Engn, CIARLab, Hong Kong, Hong Kong, Peoples R China
[2] N China Elect Power Univ, Key Lab Power Syst Protect & Dynam Secur Monitori, Minist Educ, Beijing 102206, Peoples R China
[3] Univ Western Australia, Sch Elect Elect & Comp Engn, Perth, WA 6009, Australia
[4] Hong Kong Polytech Univ, Dept Math, Hong Kong, Hong Kong, Peoples R China
来源：
IEEE TRANSACTIONS ON POWER SYSTEMS | 2009年 / 24卷 / 02期
关键词：
Latin hypercube sampling; Monte Carlo simulation; probabilistic load flow calculation; uncertainty; OPTIMAL POWER-FLOW;
D O I：
10.1109/TPWRS.2009.2016589
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Monte Carlo simulation method combined with simple random sampling (SRS) suffers from long computation time and heavy computer storage requirement when used in probabilistic load flow (PLF) evaluation and other power system probabilistic analyses. This paper proposes the use of an efficient sampling method, Latin hypercube sampling (LHS) combined with Cholesky decomposition method (LHS-CD), into Monte Carlo simulation for solving the PLF problems. The LHS-CD sampling method is investigated using IEEE 14-bus and 118-bus systems. The method is compared with SRS and LHS only with random permutation (LHS-RP). LHS-CD is found to be robust and flexible and has the potential to be applied in many power system probabilistic problems.
引用
收藏
页码：661 / 667
页数：7
相关论文
共 50 条
  • [1] Probabilistic Load Flow Evaluation With Hybrid Latin Hypercube Sampling and Multiple Linear Regression
    Xu, Xiaoyuan
    Yan, Zheng
    2015 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, 2015,
  • [2] A probabilistic load flow calculation method with latin hypercube sampling
    Yu, Han
    Chung, Chiyong
    Wong, Kitpo
    Zhang, Jianhua
    Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2009, 33 (21): : 32 - 35
  • [3] Probabilistic load flow computation using Copula and Latin hypercube sampling
    Cai, Defu
    Shi, Dongyuan
    Chen, Jinfu
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2014, 8 (09) : 1539 - 1549
  • [4] Probabilistic load flow computation with polynomial normal transformation and Latin hypercube sampling
    Cai, Defu
    Shi, Dongyuan
    Chen, Jinfu
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2013, 7 (05) : 474 - 482
  • [5] Probabilistic Load Flow using Latin Hypercube Sampling with Dependence for Distribution Networks
    Cao, Jun
    Du, W.
    Wang, H. F.
    Xiao, L. Y.
    2011 2ND IEEE PES INTERNATIONAL CONFERENCE AND EXHIBITION ON INNOVATIVE SMART GRID TECHNOLOGIES (ISGT EUROPE), 2011,
  • [6] Probabilistic Load Flow Method Based on Nataf Transformation and Latin Hypercube Sampling
    Chen, Yan
    Wen, Jinyu
    Cheng, Shijie
    IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2013, 4 (02) : 294 - 301
  • [7] Probabilistic Load Flow Method Based on Modified Latin Hypercube-Important Sampling
    Li, Quan
    Wang, Xin
    Rong, Shuaiang
    ENERGIES, 2018, 11 (11)
  • [8] Probabilistic load flow calculation method based on polynomial normal transformation and Latin hypercube sampling
    Chen, J. (chenjinfu@mail.hust.edu.cn), 1600, Chinese Society for Electrical Engineering (33):
  • [9] Probabilistic Load Flow Computation Using Non-positive Definite Correlation Control and Latin Hypercube Sampling
    Xu Q.
    Yang Y.
    Huang Y.
    Liu J.
    Wei P.
    Yang, Yang (yangyang9296@163.com), 2018, Science Press (44): : 2292 - 2299
  • [10] Cumulant method based on Latin hypercube sampling for calculating probabilistic power flow
    Huang Y.
    Xu Q.
    Bian H.
    Liu J.
    Dianli Zidonghua Shebei/Electric Power Automation Equipment, 2016, 36 (11): : 112 - 119
12345