2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC) 2016
DOI: 10.1109/eeeic.2016.7555851
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A probabilistic estimation for dynamic thermal rating of transmission lines

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Cited by 13 publications
(7 citation statements)
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“…At a first glance, the error distributions for all weather parameters do not seem to belong to a normal Gaussian distribution, as usually assumed in the literature [18,19,23,24]. We have tested this hypothesis using the Kolmogorov-Smirnov normality test.…”
Section: Weather Datamentioning
confidence: 92%
See 1 more Smart Citation
“…At a first glance, the error distributions for all weather parameters do not seem to belong to a normal Gaussian distribution, as usually assumed in the literature [18,19,23,24]. We have tested this hypothesis using the Kolmogorov-Smirnov normality test.…”
Section: Weather Datamentioning
confidence: 92%
“…the weather forecast uncertainty, is transformed into uncertainty of the predicted ampacity. This approach was proposed for the first time in [22] and then further developed by other researchers [18,19,23,24]. Nevertheless, in these papers, the meteorological data was assumed to follow a priori Gaussian distribution, which is a strong assumption not supported by real data observations.…”
Section: Introductionmentioning
confidence: 99%
“…In this context, the idea of using a Monte Carlo technique to draw possible deviations with respect to weather forecasts is not new. This approach was proposed for the first time in [21] and then further developed by other researchers, as in [22], [23] and [24]. Nevertheless, in such papers the different weather scenarios were generated assuming only Gaussian PDFs, moreover predefined a priori and not tuned on the real forecasting errors actually made by TSOs during DTR calculations.…”
Section: Introductionmentioning
confidence: 99%
“…Based on these considerations, the present paper proposes to adopt a Monte Carlo technique to generate realistic weather scenarios to be used as an input of the thermo-mechanical model of a transmission line, in order to assess the impact of weather uncertainty on the confidence intervals of thermal and mechanical outputs (conductor's temperature, tensions, sags). More in detail, as in [22], [23] and [24] the PDFs of weather parameters are firstly used to feed a thermal model of the line, thus obtaining the corresponding PDF of the conductor's temperature. As first significant novelty of our paper, we propose that the PDF of conductor's temperature is in turn used to feed a multi-span mechanical model of the line, so as to calculate the corresponding PDFs of sags, span by span.…”
Section: Introductionmentioning
confidence: 99%
“…In 2008, the Joint Committee on Measurement Guidelines introduced a supplemental document. The Monte Carlo method (MCM) was used to assess measurement uncertainty [11][12][13]. According to the supplementary document, measurement uncertainty with the MCM is newly issued in China, which provides a method for assessing the uncertainty of measurement, thus broadening the application scope of uncertainty assessment.…”
Section: Introductionmentioning
confidence: 99%