On Dispatching Line Ampacities of Power Grids Using Weather-Based Conductor Temperature Forecasts

Abstract

Finding ways to improve the line ampacity supplied by existing power grids is an inevitable problem that electricity dispatch operators are now facing. Generally, the overhead power grid can operate at a proper rating when the weather dependant dynamic thermal rating (DTR) of lines is provided. A comprehensive understanding of future variation of line temperature is necessary and useful for line operators to decide a proper dispatch measure. However, line operators usually lack real-time DTR information. Thus, this paper proposes a principal component regression (PCR)-based method, which can predict the DTR of lines by only using the weather data forecasted by meteorological stations. The possible thermal bottlenecks at different locations along the line and the margin of line ampacity can be real-time determined by the proposed PCR-based prediction method. A case study of the 161 kV transmission grid of TaiPower in Taiwan is utilized to examine the performance of the proposed forecasting model. The experimental results show that the proposed method is useful to enhance line ampacity of the power grids without installing any costly sensing instruments.