• Title/Summary/Keyword: SCBEMA curve

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An Assessment Method for Voltage Sag in Power Distribution System using a Fuzzy Model (퍼지 모델을 이용한 배전 계통에서의 순간전압강하 평가 방식)

  • Yun, Sang-Yun;O, Jeong-Hwan;Kim, Eon-Seok;Kim, Nak-Gyeong;Kim, Jae-Cheol
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.49 no.4
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    • pp.177-184
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    • 2000
  • In this paper, we proposes a method for assessing the effect of voltage sag in power distribution systems using fuzzy model. The proposed method is based on the reliability data of distribution system and specified computer business equipment manufacturer association(SCBEMA) curve that express the representative power acceptability curve by voltage sag for each customer type. The SCBEMA curves are made by using the CBEMA curves obtained from the experiment for the customers sensitive equipment. In order to transform SCBEMA curves to the differential damage by voltage sag, a fuzzy model is used. The proposed fuzzy model is composed to reflect two parameters of customers damage by voltage sag. One is the duration and magnitude of voltage sag and the other is the different risk due to the customer types. The Monte Carlo simulation method and the historical reliability data in KEPCO ae used for case studies.

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Assessing the Effect of Voltage Sag in Distribution System Using a Fuzzy Risk Assessment Model (퍼지 위험도 평가 모델을 이용한 배전계통의 순간전압강하 영향 평가)

  • Yun, Sang-Yun;Oh, Jung-Hwan;Han, Byung-Duk;Kim, Jae-Chul;Park, Joong-Shin;Lim, Dong-Gyun
    • Proceedings of the KIEE Conference
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    • 1999.07c
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    • pp.1085-1087
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    • 1999
  • In this paper, we propose the method for assessing the effect of voltage sag in power distribution system using fuzzy risk assessment model. The proposed method is based on SCBEMA curve that expresses the representative susceptibility curve by voltage sag for each customer type. These corves are made using the CBEMA curves obtained from the experiment for the customers'sensitive equipment. In order to transform SCBEMA curves to the probability damage by voltage sag, the fuzzy risk assessment model is used in this paper. Case studies were performed to analyze the effect of voltage sag by varying parameters. The Monte Carlo simulation method and the historical reliability data in KEPCO are used for case studies.

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