Fast loss allocation in bilateral open access environment using artificial neural networks

Author

Raoofat, M. ; Kargarian, A.

Author_Institution

Dept. of Power & Control Eng, Shiraz Univ, Shiraz, Iran

fYear

2009

fDate

10-12 Nov. 2009

Firstpage

1

Lastpage

5

Abstract

This paper presents a new fast algorithm to calculate the loss quota of any bilateral transaction in a deregulated environment. The method is based on the well known incremental transmission loss allocation method. While the base method is very slow to allocate loss into bilateral contracts, the proposed method uses artificial neural network to overcome this problem. The proposed method is tested on IEEE RTS 24-bus network with satisfactory results.

Keywords

Monte Carlo methods; electricity supply industry deregulation; neural nets; Monte Carlo simulation; artificial neural networks; bilateral open access environment; fast loss allocation; incremental transmission loss allocation method; Artificial neural networks; Contracts; Power generation; Power markets; Power supplies; Power system reliability; Power systems; Procurement; Propagation losses; Testing; Incremental transmission loss allocation (ITLA); Monte Carlo simulation; Online transmission loss allocation (OTLA); artificial neural networks (ANN); bilateral contracts;

fLanguage

English

Publisher

ieee

Conference_Titel

Electric Power and Energy Conversion Systems, 2009. EPECS '09. International Conference on

Conference_Location

Sharjah

Print_ISBN

978-1-4244-5477-8

Type

conf

Filename

5415691