A comparison study between artificial neural networks and AR models, applied to Norwegian inflow time series

Author

Schjolberg, Ingrid

Author_Institution

SINTEF, Trondheim, Norway

Volume

6

fYear

2000

fDate

2000

Firstpage

208

Abstract

Presents the use of artificial neural networks (ANN) and autoregressive models (AR models) as runoff models for application in the Norwegian hydro scheduling system. The main aim of the work is to investigate the performance of the different models applied to inflow time series. Improved performance of the runoff models gives better scheduling and better energy economics. The main contribution of this work is the application of these types of models in identifying daily and weekly inflow in Norwegian hydro electric power systems. The models are applied to single and multivariate systems

Keywords

autoregressive processes; neural nets; power generation economics; power generation planning; tidal power stations; time series; AR models; Norwegian hydro electric power systems; Norwegian hydro scheduling system; Norwegian inflow time series; artificial neural networks; autoregressive models; daily inflow; runoff models; weekly inflow; Artificial neural networks; Electronic mail; Mathematical model; Neural networks; Power generation economics; Power system dynamics; Power system economics; Power system modeling; Predictive models; Scheduling algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on

Conference_Location

Como

ISSN

1098-7576

Print_ISBN

0-7695-0619-4

Type

conf

DOI

10.1109/IJCNN.2000.859398

Filename

859398