NDLI: Power System Reactive Power Optimization Based on Adaptive Particle Swarm Optimization Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Sun Shuqin Zhang Bingren Wang Jun Yang Nan Meng Qingyun
Copyright Year	2013
Description	Author affiliation: Coll. of Instrum. & Electr. eEngineering, Jilin Univ., Changchun, China (Sun Shuqin; Zhang Bingren; Wang Jun; Yang Nan; Meng Qingyun)
Abstract	Aiming at the control variables of reactive power optimization are discrete, and some parameters in the standard particle swarm optimization (PSO) algorithm need to be predefined by test, so the algorithm's practicability is restricted. For these reasons, an adaptive particle swarm optimization (APSO) algorithm is proposed by the authors. APSO introduces the self-adaptive tuning strategy and boundary constraint conditions can find the global optimal solution and solve the discrete variables. The reactive power optimization results of the standard IEEE-30-bus power system show that APSO is efficient than standard PSO. The global convergence accuracy and convergence stability is obviously improved compared with that of PSO.
Starting Page	935
Ending Page	939
File Size	164740
Page Count	5
File Format	PDF
ISBN	9780769550169
DOI	10.1109/ICDMA.2013.408
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Reactive power Power system; Reactive power optimization; Particle swarm optimization;Self-adaptive tuning strategy Sociology Power system stability Particle swarm optimization Optimization Tuning Convergence
Content Type	Text
Resource Type	Article

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