Title :
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
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;
Conference_Titel :
Power Engineering Society General Meeting, 2007. IEEE
Conference_Location :
Tampa, FL
Print_ISBN :
1-4244-1296-X
Electronic_ISBN :
1932-5517
DOI :
10.1109/PES.2007.385782
