Genetic Algorithm-Based Artificial Neural Network for Voltage Stability Assessment
Joint Authors
Singh, Garima
Srivastava, Laxmi
Source
Advances in Artificial Neural Systems
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-07-31
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
With the emerging trend of restructuring in the electric power industry, many transmission lines have been forced to operate at almost their full capacities worldwide.
Due to this, more incidents of voltage instability and collapse are being observed throughout the world leading to major system breakdowns.
To avoid these undesirable incidents, a fast and accurate estimation of voltage stability margin is required.
In this paper, genetic algorithm based back propagation neural network (GABPNN) has been proposed for voltage stability margin estimation which is an indication of the power system's proximity to voltage collapse.
The proposed approach utilizes a hybrid algorithm that integrates genetic algorithm and the back propagation neural network.
The proposed algorithm aims to combine the capacity of GAs in avoiding local minima and at the same time fast execution of the BP algorithm.
Input features for GABPNN are selected on the basis of angular distance-based clustering technique.
The performance of the proposed GABPNN approach has been compared with the most commonly used gradient based BP neural network by estimating the voltage stability margin at different loading conditions in 6-bus and IEEE 30-bus system.
GA based neural network learns faster, at the same time it provides more accurate voltage stability margin estimation as compared to that based on BP algorithm.
It is found to be suitable for online applications in energy management systems.
American Psychological Association (APA)
Singh, Garima& Srivastava, Laxmi. 2011. Genetic Algorithm-Based Artificial Neural Network for Voltage Stability Assessment. Advances in Artificial Neural Systems،Vol. 2011, no. 2011, pp.1-9.
https://search.emarefa.net/detail/BIM-479292
Modern Language Association (MLA)
Singh, Garima& Srivastava, Laxmi. Genetic Algorithm-Based Artificial Neural Network for Voltage Stability Assessment. Advances in Artificial Neural Systems No. 2011 (2011), pp.1-9.
https://search.emarefa.net/detail/BIM-479292
American Medical Association (AMA)
Singh, Garima& Srivastava, Laxmi. Genetic Algorithm-Based Artificial Neural Network for Voltage Stability Assessment. Advances in Artificial Neural Systems. 2011. Vol. 2011, no. 2011, pp.1-9.
https://search.emarefa.net/detail/BIM-479292
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-479292