DocumentCode :
1535297
Title :
Improved particle swarm optimisation for multi-objective optimal power flow considering the cost, loss, emission and voltage stability index
Author :
Niknam, Taher ; Narimani, Mohammad ; Aghaei, Jamshid ; Azizipanah-Abarghooee, Rasoul
Author_Institution :
Dept. of Electron. & Electr. Eng., Shiraz Univ. of Technol., Shiraz, Iran
Volume :
6
Issue :
6
fYear :
2012
fDate :
6/1/2012 12:00:00 AM
Firstpage :
515
Lastpage :
527
Abstract :
The study presents an improved particle swarm optimisation (IPSO) method for the multi-objective optimal power flow (OPF) problem. The proposed multi-objective OPF considers the cost, loss, voltage stability and emission impacts as the objective functions. A fuzzy decision-based mechanism is used to select the best compromise solution of Pareto set obtained by the proposed algorithm. Furthermore, to improve the quality of the solution, particularly to avoid being trapped in local optima, this study presents an IPSO that profits from chaos queues and self-adaptive concepts to adjust the particle swarm optimisation (PSO) parameters. Also, a new mutation is applied to increase the search ability of the proposed algorithm. The 30-bus IEEE test system is presented to illustrate the application of the proposed problem. The obtained results are compared with those in the literatures and the superiority of the proposed approach over other methods is demonstrated.
Keywords :
Pareto optimisation; air pollution control; decision theory; fuzzy set theory; load flow; particle swarm optimisation; power system stability; IEEE bus test system; IPSO method; OPF problem; Pareto set solution; chaos queues; fuzzy decision-based mechanism; improved particle swarm optimisation; multiobjective optimal power flow; objective functions; self-adaptive concepts; voltage stability index;
fLanguage :
English
Journal_Title :
Generation, Transmission & Distribution, IET
Publisher :
iet
ISSN :
1751-8687
Type :
jour
DOI :
10.1049/iet-gtd.2011.0851
Filename :
6213709
Link To Document :
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