Extreme Quantiles Dynamic Line Rating Forecasts and Application on Network Operation

Abstract

This paper presents a study on dynamic line rating (DLR) forecasting procedure aimed at developing a new methodology able to forecast future ampacity values for rare and extreme events. This is motivated by the belief that to apply DLR network operators must be able to forecast their values and this must be based on conservative approaches able to guarantee the safe operation of the network. The proposed methodology can be summarised as follows: firstly, probabilistic forecasts of conductors’ ampacity are calculated with a non-parametric model, secondly, the lower part of the distribution is replaced with a new distribution calculated with a parametric model. The paper presents also an evaluation of the proposed methodology in network operation, suggesting an application method and highlighting the advantages. The proposed forecasting methodology delivers a high improvement of the lowest quantiles’ reliability, allowing perfect reliability for the 1% quantile and a reduction of roughly 75% in overconfidence for the 0.1% quantile.

Reliable Provision of Ancillary Services from Aggregated Variable Renewable Energy Sources through Forecasting of Extreme Quantiles

“…The issue of improving forecast reliability for extreme values is increasingly important in power systems. Recently solutions have been proposed for different applications such as setting transmission transfer capacity [5], forecasting overhead conductor ampacity [7] and wind production [6].…”