Time series and neural networks for short- time electric consumptions forecast

Promoting both energy savings and renewable energy development are two objectives of the actual and national French energy policy. In this sense, the present work takes part in a global development of various tools allowing managing energy demand. So, this paper is focused on estimating short-time electric consumptions for the city of Perpignan (south of France) by means of time series analysis, Kohonen self-organizing map and multi-level perceptron neural networks. The analysis of the results allowed determining the most effective method. Future work will focus on integrating a forecast module based on the present work in a virtual power plant.