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Abstract

This article describes research that aims to realize a real-time rating (RTR) system for power system components. The RTR technology is regarded with interest due to its potential to unlock network power transfer capacity, improve power flow congestion management flexibi-lity, and facilitate the connection of distributed generation. The solution described in this work involves the use of a limited number of meteorological stations and a series of analytical models for estimating component ratings. The effect of data uncertainty is taken into account by an estimation algorithm based on the Monte Carlo method. Estimations of conductor temperature and environmental conditions have been validated against measured data in five different network locations. Average errors of-2.2,-1.9,-1.2,-1.9, and 1.4 °C were found for the five different network locations over a period of 71 days when comparing estimates to measured results. Results analysis identified that the models used were the main source of error. The estimation of wind direction and solar radiation was the most sensitive to errors in the models. Therefore, suggestions are made regarding the improvement of these models and the RTR estimation system.

Keywords

overhead line real-time rating Monte Carlo validation

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Overhead line real-time rating estimation algorithm: Description and validation

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