Daily electrical power curves: Classification and forecasting using a Kohonen map

Abstract

This paper addresses an extensively studied problem: how to forecast the daily half-hour electrical power curve. Many methods have been developed, classical linear methods (like ARIMA methods) as well as neural ones. In this paper, we present a very simple method: the past daily curves are normalized and one considers the corresponding profile (with mean 0 and variance 1). These profiles are classified using a Kohonen map. Then, for some future point, a strategy is defined in order to compute its typical profile, the mean and the variance are forecast and the expected power curve is computed. This method uses little computation time and is easy to develop. The first results are satisfactory and promising.