Short-Time Thermal Ratings for Bare Overhead Conductors

Davidson, Glenn A.; Donoho, Thomas E.; Landrieu, Pierrer R. H.; McElhaney, Robert T.; Saeger, John H.

doi:10.1109/tpas.1969.292306

Cited by 33 publications

(8 citation statements)

References 3 publications

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“…During these tests series, the air temperature was maintained around - The coefficient M and exponent z are presented in Table 7-4. Figure 7.13 shows the measurement results for different test conductors, as well the correlations found in the literature [10], [13], [21], [35], and [38]. Re 100000 Figure 7.13 Nu numbers calculated in this study (with superscript ***) and those found in literature [10], [13], [21], [35], and [38], versus Reynolds number.…”

Section: Overall Heat Transfer Coefficientsupporting

confidence: 64%

“…. 147 13 Nu numbers calculated in this study (with superscript ***) and those found in literature [10], [13], [21], [35], and [38], versus Reynolds number 161 LIST OF TABLES Table 2-1 Melting period durations obtained for 20 mm ice layer on Bersfort conductor under 1000 A electric current and air temperature of 10 °C. The initial thermal condition for the ice-conductor composite was -10 °C 12 Table 4-1 Estimated accuracy of measured parameters 45 Table 4-2 Calculated maximal errors of the established minimum current 47 Table 6-2 Atmospheric and current parameters during ice melting with calculated energy 125 Table 7-1 Correlations for overall heat transfer coefficients 139 Table 7-2 Geometrical parameters of ACSRs 153 Table 7-3 Estimated accuracy of measured parameters 157 Table 7-4 Constants of Eq.…”

Section: Mise En Garde/advicementioning

confidence: 89%

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Modelling and simulation of the ice melting process on a current-carrying conductor =

Péter¹

2006

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Section: Overall Heat Transfer Coefficientsupporting

confidence: 64%

Section: Mise En Garde/advicementioning

confidence: 89%

Modelling and simulation of the ice melting process on a current-carrying conductor =

Péter¹

2006

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“…In 1958, House and Tuttle at Alcoa Research Laboratories (USA) suggested the steady state ampacity model [11], which is basically the one currently used. About ten years later, Morgan [12] at the National Standards Laboratory of Sydney (AU) proposed a similar steadystate rating model, while [13,14] at Jersey Central Power (USA) proposed dynamic models for describing the thermal behaviour of conductors. These models are the basis of the International Council for Large Electric Systems (CIGRE) [1] and Institute of Electrical and Electronics Engineers (IEEE) [15] models still broadly used today.…”

Section: Historical and Practical Perspectivesmentioning

confidence: 99%

Forecasting for dynamic line rating

Michiorri

Nguyen

Alessandrini

et al. 2015

Renewable and Sustainable Energy Reviews

134

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International audienceThis paper presents an overview of the state of the art on the research on Dynamic Line Rating forecasting. It is directed at researchers and decision-makers in the renewable energy and smart grids domain, and in particular at members of both the power system and meteorological community. Its aim is to explain the details of one aspect of the complex interconnection between the environment and power systems. The ampacity of a conductor is defined as the maximum constant current which will meet the design, security and safety criteria of a particular line on which the conductor is used. Dynamic Line Rating (DLR) is a technology used to dynamically increase the ampacity of electric overhead transmission lines. It is based on the observation that the ampacity of an overhead line is determined by its ability to dissipate into the environment the heat produced by Joule effect. This in turn is dependent on environmental conditions such as the value of ambient temperature, solar radiation, and wind speed and direction. Currently, conservative static seasonal estimations of meteorological values are used to determine ampacity. In a DLR framework, the ampacity is estimated in real time or quasi-real time using sensors on the line that measure conductor temperature, tension, sag or environmental parameters such as wind speed and air temperature. Because of the conservative assumptions used to calculate static seasonal ampacity limits and the variability of weather parameters, DLRs are considerably higher than static seasonal ratings. The latent transmission capacity made available by DLRs means the operation time of equipment can be extended, especially in the current power system scenario, where power injections from Intermittent Renewable Sources (IRS) put stress on the existing infrastructure. DLR can represent a solution for accommodating higher renewable production whilst minimizing or postponing network reinforcements. On the other hand, the variability of DLR with respect to static seasonal ratings makes it particularly difficult to exploit, which explains the slow take-up rate of this technology. In order to facilitate the integration of DLR into power system operations, research has been launched into DLR forecasting, following a similar avenue to IRS production forecasting, i.e. based on a mix of statistical methods and meteorological forecasts. The development of reliable DLR forecasts will no doubt be seen as a necessary step for integrating DLR into power system management and reaping the expected benefits

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“…A method of determining the duration for different short time thermal ratings has been discussed in [3,7,81. The developed expert system computes the conductor temperature as a function of time as described beloy.…”

Section: Short Time Thermal Ratingsmentioning

confidence: 99%

Expert system application for the loading capability assessment of transmission lines

Negnevitsky

Piekutowski

1995

IEEE Trans. Power Syst.

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This paper describes the application of an expeirt system for the evaluation of the short time thermal rating and temperature rise of overhead conductors.The expert system has been developed using a database and Leonard0 expert system shell which is gaining popularity among commercial tools for developing expert system applications. The expert system has been found to compare well when evaluated against the site tests. A practical application is given to demonstrate the usefulness of the expert system developed.

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Short-Time Thermal Ratings for Bare Overhead Conductors

Cited by 33 publications

References 3 publications

Modelling and simulation of the ice melting process on a current-carrying conductor =

Modelling and simulation of the ice melting process on a current-carrying conductor =

Forecasting for dynamic line rating

Expert system application for the loading capability assessment of transmission lines

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