DocumentCode :
682412
Title :
Multi-objective reactive power optimization based on chaos particle swarm optimization algorithm
Author :
He Xiao ; Pang Xia ; Zhu Da-rui ; Liu Chong-xin
Author_Institution :
Sch. of Electr. Eng., Xi´an Jiaotong Univ., Xi´an, China
fYear :
2013
fDate :
23-24 Dec. 2013
Firstpage :
1014
Lastpage :
1017
Abstract :
Reactive power optimization is closely related to voltage quality, network loss and it has great significance for the safety, reliability and economical operation of the power system. For shortage of traditional reactive power optimization, this paper establishes a multiple-objective reactive power optimization model which consists of minimum active power loss, minimum node voltage deviation, best static voltage stability and minimum reactive cost. To optimize four targets simultaneously, this paper has proposed a multi-objective reactive power optimization method which applies the chaotic particle swarm optimization algorithm based on Pareto solutions and finds the Pareto optimal solution sets of multi-objective optimization problems, then policy makers can make a scientific decision according to the actual situation. To prove the validity of the method proposed, this paper makes a multiple-objective reactive power optimization analysis for the IEEE30-bus system. The result shows that the method presented in this paper can achieve good results of reactive power optimization for decision makers to refer to.
Keywords :
Pareto optimisation; electrical safety; particle swarm optimisation; power distribution reliability; reactive power; IEEE30-bus system; Pareto optimal solution; chaos particle swarm optimization algorithm; multiobjective reactive power optimization; node voltage deviation; power network loss; power system economical operation; power system reliability; power system safety; static voltage stability; voltage quality; Chaos; Minimization; Pareto optimization; Particle swarm optimization; Power system stability; Reactive power; Chaos optimized; Multi-objective optimization; Pareto solutions; Particle swarm algorithm; Reactive power optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement, Sensor Network and Automation (IMSNA), 2013 2nd International Symposium on
Conference_Location :
Toronto, ON
Type :
conf
DOI :
10.1109/IMSNA.2013.6743453
Filename :
6743453
Link To Document :
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