Dynamic Thermal Line Ratings, Part II - Conductor Temperature Sensor and Laboratory Field Test Evaluation

Foss,; Lin, Kun-You; Stillwell,; Fernandes, Manuel A.

doi:10.1109/mper.1983.5518925

Cited by 7 publications

(6 citation statements)

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“…Research continued with the group of Foss, Lin and Maraio at General Electric (USA) [21][22][23]10] who in the years 1983-1992 further developed the models and studied their dependence on each variable. Foss and Maraio [23] also reports the results of one of the first monitoring campaigns of the temperature of different points on an overhead line, and proposes the first method for DLR forecasting based on weather forecasts.…”

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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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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“…The first commercial system based on conductor temperature monitoring, the Power Donut, was developed in the early eighties [7][8]. Besides monitoring the conductor temperature, the Power Donut monitors the current intensity.…”

Section: Conductor Temperature Monitoring Systemsmentioning

confidence: 99%

“…The conductor temperature can be measured directly [7][8][9][10] or it can be obtained indirectly from other magnitudes such as the conductor tension [11][12][13][14][15] or the sag [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Influence of the conductor temperature error on the overhead line ampacity monitoring systems

Albizu

Fernández

Mazón

et al. 2011

IET Gener. Transm. Distrib.

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“…Methods based on weather measurements [14] or conductor temperature monitoring [15,16] have been used. However, due to the uncertainties of these methods, modern methods are based on either tension [17,18] or sag [19] measurements.…”

Section: Real Time Monitoringmentioning

confidence: 99%

“…Examples that correspond to different countries, such as Spain [14], USA [15,[17][18][19], Japan [16], New Zealand [17,18] and Denmark [18] are shown.…”

Section: Real Time Monitoringmentioning

confidence: 99%

Methods for increasing the rating of overhead lines

Albizu

Mazón

Zamora

2005

2005 IEEE Russia Power Tech

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Abstract-At the present time, there is great pressure to increase the power flow in existing right of ways using existing infrastructure as far as possible. In this paper, the diverse options for increasing the rating of overhead lines are presented and analyzed. By means of a comparative study, their advantages and drawbacks are highlighted. In addition, the factors that determine the choice of the method are analyzed.

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Dynamic Thermal Line Ratings, Part II - Conductor Temperature Sensor and Laboratory Field Test Evaluation

Cited by 7 publications

References 0 publications

Forecasting for dynamic line rating

Forecasting for dynamic line rating

Influence of the conductor temperature error on the overhead line ampacity monitoring systems

Methods for increasing the rating of overhead lines

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