DocumentCode :
1847929
Title :
Congestion management based optimization technique using bee colony
Author :
Rahim, M.A. ; Musirin, I. ; Abidin, I.Z. ; Othman, M.M. ; Joshi, D.
fYear :
2010
fDate :
23-24 June 2010
Firstpage :
184
Lastpage :
188
Abstract :
Congestion management problem is a popular issue in power system which can be due to line, voltage and thermal constraints. This phenomenon can possibly lead to voltage instability occurrence, loss increment and voltage drop in power system. Therefore, a proper management of congestion should be carried appropriately in order to maintain system operability considering all the available constraints. This paper presents congestion management problem using bee colony optimization approach. The aim of the study is to optimize the cost of generation in power system network within the given available constraints. The study involved the development of bee colony algorithm in addressing congestion management, considering cost optimization as the objective function. Line constraint is also taken into consideration in this study which depends on the electrical power provider to allow the power delivered to the customers. Tests conducted on the IEEE 30-Bus Reliability Test System for performance assessment revealed that the proposed bee algorithm technique is better than evolutionary programming technique in addressing this problem.
Keywords :
optimisation; power markets; power transmission economics; power transmission reliability; IEEE 30-bus reliability test system; bee colony optimization; congestion management problem; cost optimization; electricity markets; evolutionary programming; line constraint; loss increment; optimization technique; power system network; voltage drop; voltage instability occurrence; Biological system modeling; Electrical engineering; Generators; Optimization; Power engineering; Power system stability; Bee colony algorithm; congestion management; cost optimization; electrical;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering and Optimization Conference (PEOCO), 2010 4th International
Conference_Location :
Shah Alam
Print_ISBN :
978-1-4244-7127-0
Type :
conf
DOI :
10.1109/PEOCO.2010.5559247
Filename :
5559247
Link To Document :
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