DocumentCode
676416
Title
Automatic reactive power and voltage control for regional power grid based on SVM
Author
Xiangxing Meng ; Guozhong Sun ; Jianxiang Li ; Haibo Liu
Author_Institution
Sch. of Autom., Harbin Eng. Univ., Harbin, China
fYear
2013
fDate
22-25 Oct. 2013
Firstpage
1
Lastpage
4
Abstract
In this paper, the traditional reactive power and voltage control problem is regarded as a multi-class classification problem, and a novel approach based on Support Vector Machine (SVM) classifier is proposed. According to the approach, the power grid operating status is classified according to the power factor and voltage at each substation and the corresponding control strategy is selected to control the capacitors and transformer taps. A naive progressive learning strategy is also presented to make sure the classifier can keep learning in the operation process. The approach is suitable for online operation. The decision results are robust and coordination operation between the substations can be achieved. A simple radial system containing three substations is used for case study. The results illustrate the effectiveness of the proposed approach.
Keywords
capacitors; control engineering computing; learning (artificial intelligence); pattern classification; power engineering computing; power grids; power system control; reactive power control; substations; support vector machines; transformers; voltage control; SVM classifier; automatic reactive power; capacitors control; control strategy; multiclass classification problem; power factor; power grid operating status; progressive learning strategy; regional power grid; simple radial system; substation; support vector machine; transformer taps control; voltage control; Capacitors; Optimization; Reactive power; Substations; Support vector machine classification; Voltage control; SVM; multi-class classification; power systems; progressive learning; reactive and voltage control;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON 2013 - 2013 IEEE Region 10 Conference (31194)
Conference_Location
Xi´an
ISSN
2159-3442
Print_ISBN
978-1-4799-2825-5
Type
conf
DOI
10.1109/TENCON.2013.6718482
Filename
6718482
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