제어로봇시스템학회논문지 (Journal of Institute of Control, Robotics and Systems)

  • 제19권1호
  • /
  • Pages.27-33
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  • 2013
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  • 1976-5622(pISSN)
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  • 2233-4335(eISSN)
제어로봇시스템학회 (Institute of Control, Robotics and Systems)
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지능형 클러스터링 기법에 기반한 풍력발전 고장 검출 시스템

A Fault Detection System for Wind Power Generator Based on Intelligent Clustering Method

  • 문대선 (군산대학교 전자정보공학부) ;
  • 김선국 (군산대학교 전자정보공학부) ;
  • 김성호 (군산대학교 제어로봇공학과)
  • 투고 : 2012.11.24
  • 심사 : 2012.12.26
  • 발행 : 2013.01.01
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초록

Nowadays, the utilization of renewable energy sources like wind energy is considered one of the most effective means of generating massive amounts of electricity. This is evident in the rapid increase of wind farms all over the world which comprise a huge number of wind turbines. However, the drawback of utilizing wind turbines is that it requires maintenance, which could be a costly operation. To keep the wind turbines in pristine condition so as to reduce downtime, the implementation of CMS (Condition Monitoring System) and FDS (Fault Detection System) is mandatory. The efficiency and accuracy of these systems are crucial in deciding when to carry out a maintenance process. In this paper, a fault detection system based on intelligent clustering method is proposed. Using SCADA data, the clustering model was trained and evaluated for its accuracy through rigorous simulations. Results show that the proposed approach is able to accurately detect the deteriorating condition of a wind turbine as it nears a downtime period.

키워드

참고문헌

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  1. A Study on the Parallel Operation Strategy of Small Wind Turbine System for Battery Charging vol.19, pp.6, 2014, https://doi.org/10.6113/TKPE.2014.19.6.549
  2. A Design for a Fuzzy Logic based Frequency Controller for Efficient wind Farm Operation vol.20, pp.2, 2014, https://doi.org/10.5302/J.ICROS.2014.13.8003
  3. APC Technique and Fault Detection and Classification System in Semiconductor Manufacturing Process vol.21, pp.9, 2015, https://doi.org/10.5302/J.ICROS.2015.15.0095