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-term electric consumptions for the city of Perpignan (south of France) by means of the Nearest Neighbor Technique (NNT) or Kohonen self-organizing map and multi-layer perceptron neural networks. The analysis of the results allowed comparing the efficiency of both used tools and methods. Future work will first focus on testing other popular tools for trying to improve the obtained results and secondly on integrating a forecast module based on the present work in a virtual power plant for managing energy sources and promoting renewable energy.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 firstname.lastname@example.org
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 email@example.com