An aggregate model applied to the short-term bus load forecasting problem

Author

Salgado, Ricardo Menezes ; Ballini, Rosangela ; Ohishi, Takaaki

Author_Institution

Sch. of Electr. & Comput. Eng., Dept. of Syst. Eng., Univ. of Campinas, Campinas

fYear

2009

fDate

15-18 March 2009

Firstpage

1

Lastpage

8

Abstract

In this paper we present a methodology based on a combination of clustering and forecasting techniques. The proposed method is built in two phases: In the first phase, a clustering algorithm is used to identify buses clusters with similar daily load profile. In the second phase we introduce an aggregate structure for to foresee each bus. The methodology was applied on bus load data from the Brazilian North/Northeast system and the results showed that the model was efficient with 2% to 4% average percentage error level on the buses. The obtained forecasting was compatible with the load safe operating levels of the Brazilian power system.

Keywords

load forecasting; matrix algebra; pattern clustering; Brazilian North-Northeast system; Brazilian power system; aggregate model; average percentage error level; clustering algorithm; short-term bus load forecasting problem; Aggregates; Clustering algorithms; Economic forecasting; Hybrid power systems; Load forecasting; Load modeling; Neural networks; Power system modeling; Predictive models; State estimation; Clustering Algorithm; Forecasting Model; Short-Term Bus Load Forecasting; Time Series Analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Systems Conference and Exposition, 2009. PSCE '09. IEEE/PES

Conference_Location

Seattle, WA

Print_ISBN

978-1-4244-3810-5

Electronic_ISBN

978-1-4244-3811-2

Type

conf

DOI

10.1109/PSCE.2009.4840223

Filename

4840223