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Cross‐border transmission line losses calculation using adaptive Monte–Carlo method.

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Název: Cross‐border transmission line losses calculation using adaptive Monte–Carlo method.
Autoři: Tolić, Ivan, Miličević, Kruno, Mujović, Saša
Zdroj: IET Science, Measurement & Technology (Wiley-Blackwell); Jul2017, Vol. 11 Issue 4, p400-405, 6p
Abstrakt: This study deals with calculation of transmission line losses. Having in mind that this type of losses, besides the line load and the other external input quantities such as atmospheric conditions, strongly depends on measurement uncertainty as well, the issue can be considered through finding the most convenient approach in calculation of measurement uncertainty. In this respect, two approaches (methods) are the most common: traditional method based on the guide to the expression of uncertainty in measurement (GUM) and the adaptive Monte–Carlo method (AMC). The study reveals the main disadvantages of the GUM, which is so far considered as a most accurate method. The observed drawbacks of the GUM can be successfully overcome by using of the AMC method. The comparison between the methods is performed on 110kV cross‐border transmission line from Croatian Transmission System Operator Ltd. The results show the great difference in the estimated variances, i.e. GUM variances are significantly overestimated what results in incorrect transmission losses allocation procedure with respect to its final financial effect. The study confirms that the AMC method is likely to be more practically suitable method for transmission line resistance and losses calculation. [ABSTRACT FROM AUTHOR]
Copyright of IET Science, Measurement & Technology (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Cross‐border transmission line losses calculation using adaptive Monte–Carlo method.
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  Data: <searchLink fieldCode="AR" term="%22Tolić%2C+Ivan%22">Tolić, Ivan</searchLink><br /><searchLink fieldCode="AR" term="%22Miličević%2C+Kruno%22">Miličević, Kruno</searchLink><br /><searchLink fieldCode="AR" term="%22Mujović%2C+Saša%22">Mujović, Saša</searchLink>
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  Data: IET Science, Measurement & Technology (Wiley-Blackwell); Jul2017, Vol. 11 Issue 4, p400-405, 6p
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study deals with calculation of transmission line losses. Having in mind that this type of losses, besides the line load and the other external input quantities such as atmospheric conditions, strongly depends on measurement uncertainty as well, the issue can be considered through finding the most convenient approach in calculation of measurement uncertainty. In this respect, two approaches (methods) are the most common: traditional method based on the guide to the expression of uncertainty in measurement (GUM) and the adaptive Monte–Carlo method (AMC). The study reveals the main disadvantages of the GUM, which is so far considered as a most accurate method. The observed drawbacks of the GUM can be successfully overcome by using of the AMC method. The comparison between the methods is performed on 110kV cross‐border transmission line from Croatian Transmission System Operator Ltd. The results show the great difference in the estimated variances, i.e. GUM variances are significantly overestimated what results in incorrect transmission losses allocation procedure with respect to its final financial effect. The study confirms that the AMC method is likely to be more practically suitable method for transmission line resistance and losses calculation. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of IET Science, Measurement & Technology (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1049/iet-smt.2016.0367
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