Dynamic thermal rating of power lines – Model and measurements in rainy conditions

Kosec, Gregor; Maksic, M.; Djurica, Vladimir

doi:10.1016/j.ijepes.2017.04.001

Cited by 33 publications

(13 citation statements)

References 16 publications

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“…The corona effect or in another way electric discharge phenomenon can occur in the high voltage TL because of the ionization of the fluid-like air surrounding the conductor that is electrically charged. This corona occurrence depends on the rate of the collision of the molecules in TL [30] and the molecule collisions in a conductor line can be increased with the increase of conductor temperature [35], [41]. Meanwhile, high temperatures can increase the molecule collision in the conductor that can increase the corona loss in the TL.…”

Section: Conductor Temperaturementioning

confidence: 99%

An Improved Dynamic Thermal Current Rating Model for PMU-Based Wide Area Measurement Framework for Reliability Analysis Utilizing Sensor Cloud System

et al. 2021

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Information technology expressively improves remote electricity measurement and monitoring. Integrating Dynamic Thermal Current Rating (DTCR) software packs with the exclusive phasor measurement-based Wide Area Measurement (WAM) framework, the remote Transmission Lines (TLs) current rating can be measured. WAM is used for data acquisition from different sensors, and also allows data transmissions and processing for which sensor cloud system (SCS) plays a vital role. DTCR with phasor-measurement based WAM framework is mainly used to analyze and determine the current ratings of overhead TLs using weather condition estimation or prediction methods. However, the recent study suggests that the accuracy of the DTCR has become an issue in the smart grid of Sarawak Energy Berhad (SEB). Hence, this article studies and discusses the relevant models and systems, and then proposes an improved thermal pi (π) model for the transmission line thermal model of DTCR software in WAM Framework. The performance of the improved π model will be distinguished from the existing thermal model. The weather factors that bring a substantial impact on the current rating is also considered, where the relevant data is monitored via different weather sensors. Besides, this study also focuses on calibrating the DTCR through phasor measurement in the WAM system, as well as the field measured data. All the data is collected from relevant sensors, and a detailed comparative analysis is provided based on the proposed model for the sake of improving the reliability of the system. The performance analysis of the thermal models is evaluated using Matlab software-based numerical analysis.INDEX TERMS Dynamic thermal current ratings, data acquisition system, information technology, phasor measurement unit, reliability, sensors, sensor cloud system, wide area measurement. NOMENCLATURE ABBREVIATIONS ACSR Aluminum Conductor Steel Rectifier CTE Conductor Temperature EvaluationThe associate editor coordinating the review of this manuscript and approving it for publication was Eyuphan Bulut .

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Section: Conductor Temperaturementioning

confidence: 99%

An Improved Dynamic Thermal Current Rating Model for PMU-Based Wide Area Measurement Framework for Reliability Analysis Utilizing Sensor Cloud System

et al. 2021

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“…However, the high cost of the monitoring equipment makes it difficult to implement [10]. Moreover, due to the randomness of meteorological data, there are some errors between the data obtained from the meteorological numerical prediction devices and real-time data, which often leads to the calculation results of DTR deviate from the actual operation [11]. In addition, the time variant of DTR increases the complexity of system operation and control [12].…”

Section: Introductionmentioning

confidence: 99%

Increasing the Utilization of Transmission Lines Capacity by Quasi-Dynamic Thermal Ratings

et al. 2019

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The power grid is under pressure to maintain a reliable supply because of constrained budgets and environmental policies. In order to effectively make use of existing transmission lines, it is important to accurately evaluate the line capacity. Dynamic thermal rating (DTR) offers a way to increase the utilization of capacity under real-time meteorological data. However, DTR relies on a number of sensors and the cost is high. Therefore, a method of improving the utilization of capacity by quasi-dynamic thermal rating (QDR) is proposed in this paper. QDR at different confidence levels and time scales is determined through the statistical analysis of line ampacity driven by key parameters, and the key parameters is identified by control variate method. In addition, the operation risk and tension loss is evaluated. The results show that QDR can increase the utilization of line capacity and in the absence of along-line measuring devices, QDR is more accurate, reliable and cost-saving. The managers can determine the appropriate confidence level according to the operation risk and tension loss that the system can bear, and shorten the time scale with the permission of the operation and control complexity.

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“…In addition to above problems, there are some errors between meteorological forecast data and real-time data due to the large fluctuation of meteorological parameters and the short variation interval, which leads to the results of DTR often deviate from the actual value [16]. The concept of quasi-dynamic thermal rating (QDR) was proposed in [17].…”

Section: Introductionmentioning

confidence: 99%

Power Transmission Congestion Management Based on Quasi-Dynamic Thermal Rating

et al. 2019

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Transmission congestion not only increases the operation risk, but also reduces the operation efficiency of power systems. Applying a quasi-dynamic thermal rating (QDR) to the transmission congestion alarm system can effectively alleviate transmission congestion. In this paper, according to the heat balance equation under the IEEE standard, a calculation method of QDR is proposed based on the threshold of meteorological parameters under 95% confidence level, which is determined by statistical analysis of seven-year meteorological data in Weihai, China. The QDR of transmission lines is calculated at different time scales. A transmission congestion management model based on QDR is established, and the transmission congestion alarm system including conductor temperature judgment is proposed. The case shows that transmission congestion management based on QDR is feasible, which improves the service life and operation flexibility of the power grid in emergencies and avoids power supply shortages caused by unnecessary trip protection.

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Dynamic thermal rating of power lines – Model and measurements in rainy conditions

Cited by 33 publications

References 16 publications

An Improved Dynamic Thermal Current Rating Model for PMU-Based Wide Area Measurement Framework for Reliability Analysis Utilizing Sensor Cloud System

An Improved Dynamic Thermal Current Rating Model for PMU-Based Wide Area Measurement Framework for Reliability Analysis Utilizing Sensor Cloud System

Increasing the Utilization of Transmission Lines Capacity by Quasi-Dynamic Thermal Ratings

Power Transmission Congestion Management Based on Quasi-Dynamic Thermal Rating

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