Improving the Accuracy and Time Interval of Predicting Ambient Parameters Applied to Dynamic Line Rating

This paper addresses wind speed prediction in the dynamic line rating (DLR) environment. We have described architecture of DLR system as well main characteristics nonlinear forecasting models, such neural and fuzzy logic networks. Described models were tested compared using real data (time series with on speed, direction, air temperature, solar radiation). The goal was to increase accuracy time short-term prediction. results show that networks outperform interval can be extended up several hours, no major compromise accuracy.