Abstract

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.

Highlights

  • In view of the challenges of new energy generation, load growth and obsolete distribution facilities, it is imperative to improve the utilization of transmission line capacity [1]

  • Using the data in this paper, the yearly seen that the thermal capacity of the transmission line is seasonally dependent, with the maximum rating under 99% confidence level obtained by the method in [15] is 741A, while it is 899A in this paper, which further illustrates the conservativeness of the calculation method in [15]

  • Based on the change of key parameters, a method for driving long time scale quasi-dynamic thermal rating (QDR) is proposed in this paper

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Summary

Introduction

In view of the challenges of new energy generation, load growth and obsolete distribution facilities, it is imperative to improve the utilization of transmission line capacity [1]. In [15], the historical data of key meteorological parameters were analyzed statistically to determine their thresholds in different confidence levels and time scales, and the QDR in corresponding time scales were calculated by using the thresholds. Based on the change of key meteorological parameters, a method for determining QDR of long time scale by statistical analysis of line ampacity is proposed in this paper. The conclusion can provide a basis for decision-making of line thermal rating method in power sector, and give some important suggestions for the selection of time scale and confidence level.

Heat Balance Equation
Quasi-dynamic Thermal Rating
Operation Risk and Tension Loss Assessment
Identification of Key Parameters
Statistical
Wind Direction
Quasi-dynamic
10. As shown in Figure
10. Determination
Findings
Discussion
Conclusions
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