Skeleton Network Reconfiguration for System Restoration in Restructured Power Industry

سال انتشار: 1390
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 1,210

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شناسه ملی سند علمی:

ICEE19_277

تاریخ نمایه سازی: 14 مرداد 1391

چکیده مقاله:

Power system restoration is an important task for system operators. Due to the importance of the problem, the ways which will be used for solving it are significant as well. One of the best methods for restoring a power system is recognition and access to the network reconfiguration. If the main skeleton-network is recognized appropriately, other parts of the network can be restored at the shortest possible time. Restructuring in power industry addnew complicated constraints to the problem of power system restoration. While this issue has been investigated by many researchers, little attention has been paid to this task in a marketbased environment. In most solving methods an index is defined to rank the network nodes. But none of the suggested indices have the comprehensiveness and also none of them considered the issues which have been dictated by the power market. This article represents a new combined index and market based method for ranking the network buses, which by applying it to different power systems; the best reconfigured network can be distinguished. Restoring other parts of the network from this skeleton network will lessen the restoration time. By using this index we can also decrease the cost of blackout and the cost of the power system restoration.This index in compare to similar indices has a better function and performs a better bus ranking for complicated power networks in market environment. Genetic algorithm is used to solve this problem. The suggested method is used to rank the buses of the IEEE 30-bus network. Results show that this method in compare with similar methods has a better performance

نویسندگان

Hamireza Jafarian

Graduate student in Ferdowsi University of Mashhad

Mostafa Rajabi Mashhadi

Deputy of research and planning of Khorasan Regional Electric Co

Mohammad Hossein Javidi

Professor Ferdowsi University of Mashhad