On the Transient Behavior of Large-Scale Distribution Networks During Automatic Feeder Reconfiguration

被引:36
|
作者
Spitsa, Vitaly [1 ]
Ran, Xuanchang [1 ]
Salcedo, Reynaldo [1 ]
Martinez, Juan F. [2 ]
Uosef, Resk Ebrahem [2 ]
de Leon, Francisco [1 ]
Czarkowski, Dariusz [1 ]
Zabar, Zivan [1 ]
机构
[1] NYU, Polytech Inst, Dept Elect & Comp Engn, Brooklyn, NY 11201 USA
[2] Edison Inc, New York, NY 10003 USA
关键词
Distribution automation; power distribution; power system modeling; smart grid; switching transients; time-domain analysis;
D O I
10.1109/TSG.2012.2186319
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
The paper presents an in-depth analysis of the automatic reconfiguration and self-healing principles of the next generation (3G) smart grid of a real metropolitan distribution network. The large network is to be divided dynamically and remotely controlled into three smaller subnetworks to further increase the reliability of electrical power distribution secondary networks. When one subsection is experiencing difficulties, there is no longer the need to de-energize the entire network. A time-domain (EMTP) model has been developed and validated by comparing simulations with recordings of actual transient events. Different switching and fault scenarios are investigated using this model. Analysis of the results provides important conclusions on equipment rating, relay protection coordination, voltage regulation, switching and operation strategies which are discussed in the paper. A subset of these results is presented for illustration. This extensive study of a complex urban network suggests that: 1) before implementation of smart grid principles, it would be prudent to supplement steady-state analysis with time-domain analysis to avoid problems, such as installation of improperly rated equipment, and improper relay-protection coordination; and 2) EMTP-type programs may be used to conduct the time-domain analysis, despite the enormous number of elements contained in an urban network.
引用
收藏
页码:887 / 896
页数:10
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