The Transactions of the Korean Institute of Electrical Engineers A (대한전기학회논문지:전력기술부문A)

The Korean Institute of Electrical Engineers (대한전기학회)
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Prediction of Dynamic Line Rating Based on Thermal Risk Probability by Time Series Weather Models

시계열 기상모델을 이용한 열적 위험확률 기반 동적 송전용량의 예측

  • 김동민 (한양대 공대 전기공학과) ;
  • 배인수 (한양대 공대 전기공학과) ;
  • 조종만 (한양대 공대 전기공학과) ;
  • 장경 (단국대 공대 산업공학과) ;
  • 김진오 (한양대 공대 전기공학과)
  • Published : 2006.07.01
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Abstract

This paper suggests the method that forecasts Dynamic Line Rating (DLR). Thermal Overload Risk Probability (TORP) of the next time is forecasted based on the present weather conditions and DLR value by Monte Carlo Simulation (MCS). To model weather elements of transmission line for MCS process, this paper will propose the use of statistical weather models that time series is applied. Also, through the case study, it is confirmed that the forecasted TORP can be utilized as a criterion that decides DLR of next time. In short, proposed method may be used usefully to keep security and reliability of transmission line by forecasting transmission capacity of the next time.

Keywords

References

  1. IEEE Standard for Calculating the Current-Tempe-rature Relationship of Bare Overhead Conductors, IEEE Standard pp.738, 1993
  2. D.A. Douglass and A.A Edris, 'Real-Time monitoring and dynamic thermal rating of power transmission circuits', IEEE Trans. on Power Delivery, Vol. 11, No.3, pp, 1407-1418, 1996 https://doi.org/10.1109/61.517499
  3. J.S Engelhardt, S.P Babu, 'Design, Installation, and Field Experience with an Overhead Transmission DLR System', Transmission and Distribution Conference, 15-20 Sept. 1996 pp. 366-370 https://doi.org/10.1109/TDC.1996.545961
  4. J. K. Raniga, R. K. Rayudu, 'Dynamic Rating of Transmission Lines-A New Zealand Experience', Power Engineering Society Winter Meeting, 23-27 Jan. 2000, IEEE Vol. 4, pp. 2403-2409 https://doi.org/10.1109/PESW.2000.847185
  5. J.F.Hall and A.K.Deb, 'Prediction of overhead transmission line ampacity by stochastic and deterministic models', IEEE Trans. on Power Delivery, Vol. 3, No.2, pp.789-800, 1988 https://doi.org/10.1109/61.4319
  6. W.J. Steeley and A.K. Deb, 'Ambient temperature correlated dynamic transmission line ratings at two PG&E location', IEEE Trans. on Power Delivery, Vol. 6, No.3, pp. 1234-1242, 1991 https://doi.org/10.1109/61.85872
  7. Jun Zhang, Jian Pu, James D. McCalley, Hal Stern. and William A Gallus, Jr. 'A Bayesian Approach for Short-Term Transmission Line Thermal Overload Risk Assessment', IEEE Trans. on Power Delivery, Vol. 17, No.3, pp. 770-778, 2002 https://doi.org/10.1109/TPWRD.2002.1022802
  8. From 1992 to 2002, DB of AWS in Korea Metrolo-gical Administration [Online]. Available: http://www.kma.go.kr/eng/index.jsp
  9. T. Seppa, 'Closure of the Panel on 'Selection of Weather Parameters for Overhead Line Ratings', IEEE PES Meeting, Denver, June 8, 2004
  10. D. Douglass, 'Wind Speed for Line Ratings Variation with Time, Sheltering & Instrumentation', IEEE PES Meeting, Denver, June 8, 2004
  11. N. I. Fisher, Statistical Analysis of Circular Data. Cambridge, U.K.: Cambridge Univ. Press. 1993
  12. 서영경, 김근현, 나득균，'동적선형모형을 이용한 3시간 기온예보 모델의 운영'，2002년 한국 기상학회지 봄 학술발표 논문집，2002