A Neural Network Based Method For Fast ATC Estimation in Electricity Markets

Author

Jain, T. ; Singh, S.N. ; Srivastava, S.C.

Author_Institution

Dept. of Electr. Eng., Indian Inst. of Technol., Kanpur

fYear

2007

fDate

24-28 June 2007

Firstpage

1

Lastpage

8

Abstract

In a competitive electricity market, available transfer capability (ATC) information is required by market participants as well as the system operator (SO) for secure operation of the power system. The on-line updating of ATC information requires a fast and accurate method for its determination. This paper proposes a multi-layer perceptron (MLP) based neural network model for ATC estimation in a competitive electricity market having bilateral as well as multilateral transactions. Relevant input features have been obtained by using a random forest (RF) technique. Levenberg-Marquardt algorithm has been used for training of neural network. The effectiveness of the proposed method has been tested on 39-bus New England System and a practical 246-bus Indian system.

Keywords

load flow; multilayer perceptrons; power engineering computing; power markets; power system security; 246-bus Indian system; 39-bus New England System; Levenberg- Marquardt algorithm; available transfer capability information; electricity markets; fast ATC estimation; market participants; multilayer perceptron based neural network model; power system security; random forest technique; Artificial neural networks; Electricity supply industry; Electronic mail; Load flow; Neural networks; Optimization methods; Power generation; Power system interconnection; Power system modeling; Voltage; Artificial neural network; available transfer capability; feature selection; multilayer perceptron; random forest technique;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Engineering Society General Meeting, 2007. IEEE

Conference_Location

Tampa, FL

ISSN

1932-5517

Print_ISBN

1-4244-1296-X

Electronic_ISBN

1932-5517

Type

conf

DOI

10.1109/PES.2007.385782

Filename

4275548