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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국정보처리학회 JIPS(Journal of Information Processing Systems) JIPS(Journal of Information Processing Systems) 제15권 제2호
- 발행연도
- 2019.1
- 수록면
- 331 - 343 (13page)
이용수
초록· 키워드
오류제보하기
Dynamic thermal rating of the overhead transmission lines is affected by many uncertain factors. The ambienttemperature, wind speed and wind direction are the main sources of uncertainty. Measurement uncertainty isan important parameter to evaluate the reliability of measurement results. This paper presents the uncertaintyanalysis based on Monte Carlo. On the basis of establishing the mathematical model and setting the probabilitydensity function of the input parameter value, the probability density function of the output value is determinedby probability distribution random sampling. Through the calculation and analysis of the transient thermalbalance equation and the steady- state thermal balance equation, the steady-state current carrying capacity, thetransient current carrying capacity, the standard uncertainty and the probability distribution of the minimumand maximum values of the conductor under 95% confidence interval are obtained. The simulation resultsindicate that Monte Carlo method can decrease the computational complexity, speed up the calculation, andincrease the validity and reliability of the uncertainty evaluation.
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참고문헌 (19)
참고문헌 신청
2013 / IEEE Standard for Calculating the Current-Temperature Relationship of Bare Overhead Conductors / IEEE Standard 738-2012
A. Michiorri / 2015 / Forecasting for dynamic line rating / Renewable and Sustainable Energy Reviews 52:1713~1730
P. Pytlak / 2011 / Using dynamic thermal rating systems to reduce power generation emissions / Proceedings of IEEE Power and Energy Society General Meeting :1~7
D. Roberts / 2008 / Dynamic thermal rating for increasing network capacity and delaying network reinforcements / CIRED Seminar 2008: Smart Grids for Distribution :1~4
G. A. Orfanos / 2013 / Transmission expansion planning of systems with increasing wind power integration / IEEE Transactions on Power Systems 28(2):1355~1362
A. Michiorri / 2015 / Forecasting for dynamic line rating / Renewable and Sustainable Energy Reviews 52:1713~1730
P. Pytlak / 2011 / Using dynamic thermal rating systems to reduce power generation emissions / Proceedings of IEEE Power and Energy Society General Meeting :1~7
D. Roberts / 2008 / Dynamic thermal rating for increasing network capacity and delaying network reinforcements / CIRED Seminar 2008: Smart Grids for Distribution :1~4
G. A. Orfanos / 2013 / Transmission expansion planning of systems with increasing wind power integration / IEEE Transactions on Power Systems 28(2):1355~1362
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