Influence of uncertainties and parameter structural dependencies in distribution system state estimation

被引:2
作者
Liao, Huilian [1 ]
Milanovic, Jovica V. [2 ]
Hasan, Kazi N. [2 ]
Tang, Xiaoqing [2 ]
机构
[1] Sheffield Hallam Univ, Power Elect & Control Engn Grp, Sheffield S1 1WB, S Yorkshire, England
[2] Univ Manchester, Sch Elect & Elect Engn, POB 88, Manchester M60 1QD, Lancs, England
基金
欧盟地平线“2020”; 英国工程与自然科学研究理事会;
关键词
power system state estimation; power distribution; sensitivity analysis; parameter structural dependencies; distribution system state estimation; efficient sensitivity analysis technique; Morris screening method; uncertain parameters; SE performance; dependence structure analysis; SE accuracy; copula; bivariate space; critical variable allocation; power system operators; monitoring accuracy; SENSITIVITY-ANALYSIS;
D O I
10.1049/iet-gtd.2017.1906
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
080906 [电磁信息功能材料与结构]; 082806 [农业信息与电气工程];
摘要
This study evaluates a number of uncertain parameters that affect the accuracy of distribution system state estimation (SE), and ranks their importance using an efficient sensitivity analysis technique, Morris screening method. The influence of the uncertain parameters on SE performance is analysed globally and zonally. Furthermore, the dependence structure between the critical variable and SE accuracy is analysed using copula to establish their relationship at different section of the bivariate space. The sensitivity of the critical parameter at different ranges is also studied and ranked using Morris screening methods to present the variation of SE performance when the critical variable is allocated at different sections within the feasible range. Accurate assessment of the importance of various uncertain parameters and the analysis of the dependence structure can inform power system operators which parameters will require the greatest levels of mitigation or increased monitoring accuracy in order to have satisfactory performance of distribution system SE.
引用
收藏
页码:3279 / 3285
页数:7
相关论文
共 29 条
[1]
Abur A., 2004, POWER SYSTEM STATE E
[2]
Distribution System State Estimation Based on Nonsynchronized Smart Meters [J].
Alimardani, Arash ;
Therrien, Francis ;
Atanackovic, Djordje ;
Jatskevich, Juri ;
Vaahedi, Ebrahim .
IEEE TRANSACTIONS ON SMART GRID, 2015, 6 (06) :2919-2928
[3]
[Anonymous], 6007612000 IEC
[4]
[Anonymous], 2012, GB ENERGY DEMAND 201
[5]
[Anonymous], 2011, HIPERDNO2011D221
[6]
[Anonymous], 2003, 610004302003 IEC
[7]
[Anonymous], P INSTR MEAS TECH C
[8]
[Anonymous], 501602004 EN
[9]
Asprou M., 2016, P IEEE POW EN SOC GE
[10]
Stochastic Modeling for the Next Day Domestic Demand Response Applications [J].
Bina, M. Tavakoli ;
Ahmadi, Danial .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2015, 30 (06) :2880-2893