NeuroDem-a neural network based short term demand forecaster

Author

Da Silva, A. P Alves ; Rodrigues, U.P. ; Reis, A. J Rocha ; Moulin, L.S.

Author_Institution

Inst. of Electr. Eng., Fed. Eng. Sch. at Itajuba, Brazil

Volume

2

fYear

2001

fDate

2001

Abstract

The application of Neural Network (NN) based short-term load forecasting (STLF) has developed to sophisticated practical systems over the years. However, the question of how to maximize the generalization ability of such machines, together with the choice of architecture, activation functions, training set data and size, etc. makes up a huge number of possible combinations for the final NN design, whose optimal solution has not been figured yet. This paper describes a STLF system (NeuroDem) which has been used by Brazilian electric utilities for 3 years. It uses a nonparametric model based on a linear model coupled with a polynomial network, identified by pruning/growing mechanisms. NeuroDem has special features of data pre-processing and confidence intervals calculations, which are also described. Results of load forecasts are presented for one year with forecasting horizons from 15 min to 168 hours ahead

Keywords

learning (artificial intelligence); load forecasting; neural nets; power consumption; power system analysis computing; 15 min to 168 hour; Brazil; NeuroDem; activation functions; architecture; confidence intervals calculations; data pre-processing; electric utilities; generalization ability; neural network; nonparametric model; polynomial network; power systems; pruning/growing mechanisms; short term demand forecaster; training set; Demand forecasting; Energy management; Engineering management; Input variables; Load forecasting; Neural networks; Power engineering and energy; Power industry; Predictive models; Systems engineering and theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Tech Proceedings, 2001 IEEE Porto

Conference_Location

Porto

Print_ISBN

0-7803-7139-9

Type

conf

DOI

10.1109/PTC.2001.964736

Filename

964736