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Python을 이용한 유전 알고리즘 기반의 수도권 고장전류 저감을 위한 BTB HVDC 최적 위치 선정 기법에 관한 연구

A Study on Selecting the Optimal Location of BTB HVDC for Reducing Fault Current in Metropolitan Regions Based on Genetic Algorithm Using Python

  • Song, Min-Seok (Dept. of Electrical Engineering, Incheon National University) ;
  • Kim, Hak-Man (Dept. of Electrical Engineering, Incheon National University) ;
  • Lee, Byung Ha (Dept. of Electrical Engineering, Incheon National University)
  • 투고 : 2017.05.29
  • 심사 : 2017.07.12
  • 발행 : 2017.08.01

초록

The problem of fault current to exceed the rated capacity of a power circuit breaker can cause a serious accident to hurt the reliability of the power system. In order to solve this issue, current limiting reactors and circuit breakers with increased capacity are utilized but these solutions have some technical limitations. Back-to-back high voltage direct current(BTB HVDC) may be applied for reducing the fault current. When BTB HVDCs are installed for reduction in fault current, selecting the optimal location of the BTB HVDC without causing overload of line power becomes a key point. In this paper, we use genetic algorithm to find optimal location effectively in a short time. We propose a new methodology for determining the BTB HVDC optimal location to reduce fault current without causing overload of line power in metropolitan areas. Also, the procedure of performing the calculation of fault current and line power flow by PSS/E is carried out automatically using Python. It is shown that this optimization methodology can be applied effectively for determining the BTB HVDC optimal location to reduce fault current without causing overload of line power by a case study.

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