Validation of a PMU-based fault location identification method for smart distribution network with photovoltaics using real-time data

被引:55
作者
Usman, Muhammad Usama [1 ,2 ]
Faruque, Md. Omar [1 ,2 ]
机构
[1] Florida State Univ, Elect & Comp Sci, 2000 Levy Ave, Tallahassee, FL 32310 USA
[2] Florida State Univ, Ctr Adv Power Syst, 2000 Levy Ave, Tallahassee, FL 32310 USA
关键词
power engineering computing; smart power grids; phasor measurement; fault location; SQL; distributed power generation; protocols; distribution networks; power system measurement; DG; PMUs; real-time model; DRTS; streams phasor data; OpenPDC; real-time PMU data; real-time simulator; store data; Matlab-based FL identification algorithm; balanced fault types; unbalanced fault types; PMU-based fault location identification method; smart distribution network; real-time data; distributed generation; state estimation algorithm; SE; simulated phasor measurement units; fault currents; generators; voltage measurements; FL algorithm; IEEE 37 node test feeder; operating distribution grid; CIRCUIT ANALYSIS;
D O I
10.1049/iet-gtd.2018.6245
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
A fault location (FL) identification method for smart distribution network is presented and validated using a digital real-time simulator (DRTS). The method can accurately identify the FL in a distribution network in the presence of distributed generation (DG). This method is based on state estimation (SE) algorithm which uses real-time data from simulated phasor measurement units (PMUs), placed in the distribution network. SE needs the fault currents of the generators and voltage measurements of an optimal number of nodes to perform the FL algorithm. The method was validated using the IEEE 37 node test feeder with DGs. PMUs are placed on the real-time model of the system. The real-time model was implemented on a DRTS which streams phasor data over the Internet using C37.118 protocol. OpenPDC is used to collect real-time PMU data coming from the DRTS. Microsoft SQL is used as a database management server to store data coming from OpenPDC. In the last step of the FL process, data stored in OpenPDC is fed into a FL identification algorithm to locate the fault. Both balanced and unbalanced fault types are applied to different nodes and an accurate estimation of the FL (over 90% of the cases) is achieved.
引用
收藏
页码:5824 / 5833
页数:10
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