Forecasting Portugal global load with artificial neural networks

• Type: Article in International Conference Proceedings Book
• Date: 2007

Authors

José Nuno Fidalgo (Author) FEUP; Manuel Matos (Author) FEUP

Conference proceedings International

Title: Artificial Neural Networks - ICANN 2007, Pt 2, Proceedings

Pages: 728-737

17th International Conference on Artificial Neural Networks (ICANN 2007)

Oporto, PORTUGAL, SEP 09-13, 2007

Indexing

ISI Web of Knowledge - 14 Citations

Scopus - 21 Citations

Other information

Authenticus ID: P-004-CJJ

DOI: 10.1007/978-3-540-74695-9_75

Abstract (EN): This paper describes a research where the main goal was to predict the future values of a time series of the hourly demand of Portugal global electricity consumption in the following day. In a preliminary phase several regression techniques were experimented: K Nearest Neighbors, Multiple Linear Regression, Projection Pursuit Regression, Regression Trees, Multivariate Adaptive Regression Splines and Artificial Neural Networks (ANN). Having the best results been achieved with ANN, this technique was selected as the primary tool for the load forecasting process. The prediction for holidays and days following holidays is analyzed and dealt with. Temperature significance on consumption level is also studied. Results attained support the adopted approach.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10