Journal of the Korean Institute of Illuminating and Electrical Installation Engineers (조명전기설비학회논문지)

The Korean Institute of IIIuminating and Electrical Installation Engineers (한국조명전기설비학회)
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Short-Term Dynamic Line Rating Prediction in Overhead Transmission Lines Using Weather Forecast System

기상예보시스템을 이용한 가공송전선의 단기간 동적송전용량 예측

  • 김성덕 (한밭대학교 전기ㆍ전자ㆍ제어공학부) ;
  • 이승수 (한밭대학교 전기ㆍ전자ㆍ제어공학부) ;
  • 장태인 (한밭대학교 전기ㆍ전자ㆍ제어공학부) ;
  • 장지원 (한밭대학교 전기ㆍ전자ㆍ제어공학부) ;
  • 이동일 (한밭대학교 전기ㆍ전자ㆍ제어공학부)
  • Published : 2004.11.01
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Abstract

A method for predicting the short-term dynamic line ratings in overhead transmission lines using real-time weather forecast data is proposed in this paper. Through some inspections for the 3-hour interval forecasting factors such as ambient temperature, wind speed grade and weather code given by KMA(Korea Meteorological Administration), correlation properties between forecast weather data and actual measured data are analyzed. To use these variable in determining the dynamic line ratings, they are changed into suitable numerical values. Furthermore adaptive neuro-fuzzy systems to improve reliabilities for wind speed and solar heat radiation ate designed It was verified that the forecast weather data can be used to predict the line rating with reliable. As a result it can be possible that the proposed predicting system can be effectively utilized by their anticipation a short-time in advance.

본 논문에서는 실시간 기상예보데이터를 사용하여 가공송전선의 단시간 송전용량을 예측하기 위한 방법을 제안한다. 기상청에서 제공되는 예보기온, 풍속등급 및 날씨코드와 같은 3시간 예보요소들을 분석하여 기상예보데이터와 실제 측정데이터 사이의 상관성이 분석되었다. 동적송전용량을 결정하는데 사용하기 위하여 이러한 요소들은 적당한 수치로 변환되었다. 또한 풍속과 일사량에 대한 신뢰도를 개선하기 위하여 적응뉴로퍼지시스템이 설계되었다. 기상예보데이터가 송전용량을 신뢰성을 갖도록 추정하는데 사용될 수 있음을 밝혔다. 그 결과 제안된 예측시스템이 단시간 용량예측에 효율적으로 실용화될 수 있을 것이다.

Keywords

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  1. Dynamic Line Rating Prediction in Overhead Transmission Lines Using Artificial Neural Network vol.28, pp.1, 2014, https://doi.org/10.5207/JIEIE.2014.28.1.079