Electricity price forecasting of the South East European power exchanges

Abstract

The deregulation of the electricity market is a process which is currently very hot topic in the Southeast European region. Namely, few of the countries have their own power exchanges from long time ago, but few of them have just formed ones and the remaining countries need to decide in the near future the direction they are going to follow towards resolving this problem. With the introduction of the power exchanges and the fact that half of the power markets in the Southeast European region exist less than one year, forecasting the electricity price on those markets is becoming very attractive research area and is of great importance. In this paper, 24-hours ahead forecasting of the electricity price in these newly formed power exchanges is. To this end, an artificial intelligence models, specifically neural networks are used in this paper, which as an input use all information that are relevant for the corresponding power exchange price forecasting. The results show that among the newly formed power exchanges in the region, the price in Bulgarian power exchange is the most unpredictable one, while, on the other hand, the price in the Serbian power exchange is the most predictable one. Additionally, the results present in which hours of the day and in which days in the week the prices have the highest variations.