Fuzzy inference in spatial load forecasting

Author

Miranda, Vladimiro ; Monteiro, Cláudio

Author_Institution

INESC, Porto, Portugal

Volume

2

fYear

2000

fDate

2000

Firstpage

1063

Abstract

Forecasting electric demand and its geographical distribution is a prerequisite to generate expansion planning scenarios for distribution planning. This paper presents a comprehensive methodology that uses a fuzzy inference model over a GIS support, to capture the behavior of influence factors on load growth patterns and map the potential for development. The load growth is spread over maps with cellular automata. The interaction with a scenario generator inputs data into a graph generator, which will serve as a basis for more classic network planning tools

Keywords

cellular automata; fuzzy logic; geographic information systems; inference mechanisms; load forecasting; power distribution planning; power system analysis computing; GIS support; cellular automata; distribution network planning; electric demand forecasting; expansion planning scenarios; fuzzy inference model; geographical distribution; graph generator; load growth patterns; scenario generator; spatial load forecasting; Design optimization; Distributed computing; Engines; Fuzzy systems; Geographic Information Systems; Load forecasting; Mesh generation; Power generation; Predictive models; Risk analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Engineering Society Winter Meeting, 2000. IEEE

Print_ISBN

0-7803-5935-6

Type

conf

DOI

10.1109/PESW.2000.850087

Filename

850087