NDLI: Optimal Location and Parameters Setting of Unified Power Flow Controller Based on Evolutionary Optimization Techniques

Content Provider	IEEE Xplore Digital Library
Author	Shaheen, H.I. Rashed, G.I. Cheng, S.J.
Copyright Year	2007
Description	Author affiliation: Coll. of Electr. & Electron. Eng., Huazhong Univ. of Sci. & Technol., Wuhan (Shaheen, H.I.; Rashed, G.I.)
Abstract	Flexible alternating current transmission systems (FACTS) devices have been proposed as an effective solution for controlling power flow and regulating bus voltage in electrical power systems, resulting in an increased transfer capability, low system losses, and improved stability. However to what extent the performance of FACTS devices can be brought out highly depends upon the location and the parameters of these devices. Unified power flow controller (UPFC) is one of the most promising FACTS devices for power flow control. In this paper, we propose two evolutionary optimization techniques, namely genetic algorithm (GA) and particle swarm optimization (PSO) to select the optimal location and the optimal parameters setting of UPFC which minimize the active power losses in the power network, and compare their performances. To show the validity of the proposed techniques and for comparison purposes, simulations are carried out on a three-bus, a five-bus, and an IEEE-14 bus test power systems. The obtained results indicate that both techniques can successfully find the optimal location and parameters setting of UPFC, but PSO is faster than GA from the time perspective.
Starting Page	1
Ending Page	8
File Size	369820
Page Count	8
File Format	PDF
ISBN	142441296X
ISSN	19325517
DOI	10.1109/PES.2007.385581
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-06-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Load flow Optimal control Power system stability Power system simulation Flexible AC transmission systems Voltage control Control systems Propagation losses Load flow control Genetic algorithms Unified Power Flow controller (UPFC) Evolutionary Optimization Techniques Genetic Algorithm (GA) Particle Swarm Optimization (PSO)
Content Type	Text
Resource Type	Article

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