Neural Networks Applied to Spatial Load Forecasting in GIS

• Type: Article in International Scientific Journal
• Date: 2004

Authors

José Nuno Fidalgo (Author) FEUP

Journal

Title: WSEAS Transactions on Circuits and Systems

Vol. 3 No. 1

ISSN: 1109-2734

Publisher: World Scientific and Engineering Academy and Society (WSEAS) Press

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

CORDIS: Technological sciences > Engineering > Electrical engineering

Other information

Abstract (EN): Quality spatial load forecasting is a major prerequisite for energy distribution systems planning. The load evolution outline depends on the urban expansion and its land usage. This paper presents a methodology for knowledge extraction of the data provided by a GIS (Geographical Information Systems) platform. The main goal consists of developing studies that lead to the understanding of the influence of geographical factors on the load growth patterns and energetic potential development. Kohonen maps and Artificial Neural Networks are used for data interpretation and spatial load forecasting purposes.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6