Impact of exogenous variables on estimated values of demand and energy

Author

Yasuoka, Jorge ; Souza, Reynaldo A., Jr. ; Jardini, José A. ; Castro, Roberto ; Prado, Fernando A A ; Brittes, Liliana M.V. ; Cruz, André L P ; Schmidt, Hernán P.

Author_Institution

Escola Politecnica, Sao Paulo Univ., Brazil

fYear

2004

fDate

8-11 Nov. 2004

Firstpage

344

Lastpage

348

Abstract

Traditional methods for estimating future values of demand and energy do not normally take into account the effect of the so-called exogenous variables, which include load geographical location, seasonal variations, availability restrictions of energy and summer time schedules. This work proposes a methodology for assessing the impact of these external variables on the estimation of future values of demand and energy, with a view to improving current practices which dictate demand and energy purchases in both the short term and the medium term. The load curve is broken into components associated with each one of the exogenous variables. The future behavior of each component is estimated through artificial neural networks and the estimated global curve is obtained by aggregating the various components back together.

Keywords

load forecasting; neural nets; power markets; power system analysis computing; artificial neural network; demand and energy; electric utility; exogenous variable; load curve; load geographical location; seasonal variation; summer time schedule; system load forecasting; Artificial neural networks; Cost function; Demand forecasting; Distributed control; Helium; Load forecasting; Marketing and sales; Optimization methods; Regression analysis; Scheduling;

fLanguage

English

Publisher

ieee

Conference_Titel

Transmission and Distribution Conference and Exposition: Latin America, 2004 IEEE/PES

Print_ISBN

0-7803-8775-9

Type

conf

DOI

10.1109/TDC.2004.1432403

Filename

1432403