DocumentCode
3215835
Title
Adaptive distance relaying scheme in presence of UPFC using WAMS
Author
Seethalekshmi, K. ; Singh, S.N. ; Srivastava, S.C.
Author_Institution
Dept. of Electr. Eng., Indian Inst. of Technol. Kanpur, Kanpur
fYear
2009
fDate
15-18 March 2009
Firstpage
1
Lastpage
6
Abstract
This paper analyses the impact of unified power flow controller (UPFC) on performance of distance relaying scheme and proposes a new adaptive relaying technique for mitigating the undesirable effects of overreach/underreach shown by the conventional distance relays. The proposed scheme computes on-line control parameters of the UPFC based on synchronized phasor measurements from Phasor Measurement Units (PMU) installed at line terminals. Trip boundaries are generated for the distance relay considering the effects of control parameters of UPFC, fault resistance and system loading condition. Moreover, for deciding the trip boundaries for a given Single Line to Ground (SLG) fault, the information on self protection mode of UPFC (bypass mode), has also been utilized. A generalized regression neural network has been used to identify the trip boundaries of the distance relay. The simulation results show the ability of the generalized regression neural network to identify the trip boundaries inspite of dynamic changes in the control parameters of the UPFC.
Keywords
control engineering computing; fault diagnosis; load flow control; neural nets; power system measurement; regression analysis; WAMS; adaptive distance relaying scheme; distance relay; fault resistance; generalized regression neural network; on-line control parameters; phasor measurement units; single line to ground fault; synchronized phasor measurements; unified power flow controller; Adaptive control; Control systems; Electrical resistance measurement; Load flow; Neural networks; Performance analysis; Phasor measurement units; Programmable control; Protective relaying; Relays; Distance relay; Flexible alternating current transmission (FACTS) controllers; Generalized regression neural network; Unified power flow controller;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Systems Conference and Exposition, 2009. PSCE '09. IEEE/PES
Conference_Location
Seattle, WA
Print_ISBN
978-1-4244-3810-5
Electronic_ISBN
978-1-4244-3811-2
Type
conf
DOI
10.1109/PSCE.2009.4840051
Filename
4840051
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