Forecasting transmission congestion

Anders Loland, Egil Ferkingstad and Mathilde Wilhelmsen

Abstract

ABSTRACT

In electricity markets, transmission congestion creates area price differences. Therefore, good forecast models for congestion are valuable in themselves, and may also improve price predictions. We study a combined measure of the net capacity utilization for one single price area, and provide hourly day-ahead forecasts for the NO1 area of Nord Pool using several different prediction models. These forecasts are combined, using average forecasts and two different types of weighted averages of forecasts.We compare the performance of the different models. In most cases, the combined transmission congestion forecasts outperform the other methods for data from 2003 to 2009.