Input Vector Comparison for Hourly Load Forecast of Small Load Area Using Artificial Neural Network

Author

Tasre, Mohan B. ; Ghate, Vilas N. ; Bedekar, Prashant P.

Author_Institution

Electr. Eng. Dept., Gov. Coll. of Eng., Amravati, Amravati, India

fYear

2012

fDate

11-13 May 2012

Firstpage

254

Lastpage

258

Abstract

This paper presents an hourly load forecast of small load area using Artificial Neural Network (ANN). For this case-study duration of February-2010 to Januray-2011 is considered. In this study ANN is trained and tested for by providing two different input vectors. In this paper the input vector design and the data is mainly focused. Also, suitable ANN topology is also discussed. Further the training and testing process for ANNs of these months are explained. Back-propagation algorithm is employed in this process. Finally by comparing network performances for these two input vectors for each of the considered month, optimum vector is selected.

Keywords

load forecasting; neural nets; power engineering computing; ANN topology; artificial neural network; back-propagation; hourly load forecast; input vector comparison; input vector design; small load area; Artificial neural networks; Forecasting; Load forecasting; Neurons; Testing; Training; Vectors; Artificial Neural Network; Back Propagation algorithm; Input Vector; Momentum learning rule; Short-term Load Forecasting;

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Systems and Network Technologies (CSNT), 2012 International Conference on

Conference_Location

Rajkot

Print_ISBN

978-1-4673-1538-8

Type

conf

DOI

10.1109/CSNT.2012.63

Filename

6200643