DocumentCode :
1922593
Title :
Estimation of voltage stability index in a power system with Plug-in Electric Vehicles
Author :
Makasa, K. Joseph ; Venayagamoorthy, Ganesh K.
Author_Institution :
Real-Time Power & Intell. Syst. Lab., Missouri Univ. of Sci. & Technol., Rolla, MO, USA
fYear :
2010
fDate :
1-6 Aug. 2010
Firstpage :
1
Lastpage :
7
Abstract :
A Multilayer Perceptron (MLP) neural network based approach for estimation of the voltage stability L-index in a power system with Plug-in Electric Vehicles (PEVs) is presented. This technique overcomes the limitations of direct calculation of L-index from measurements at a load bus. The L-index calculation is dependent upon the no-load voltage phasor for any given system topology and operating condition. In practice it is difficult to obtain no-load voltage phasor at a bus each time the system topology or operating point changes. An MLP neural network based method capable of estimating voltage stability L-index at a load bus using direct measurements and that does is independent of the no-load voltage phasor of the bus is presented. Results show that the MLP accurately estimates the voltage stability L-index for different cases of system topologies and operating conditions.
Keywords :
electric vehicles; load (electric); multilayer perceptrons; power system analysis computing; power system planning; power system stability; voltage control; MLP neural network; load bus; multilayer perceptron neural network; no load voltage phasor; plug-in electric vehicles; voltage stability L-index estimation; Artificial neural networks; Estimation; Power system stability; Stability criteria; Voltage measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bulk Power System Dynamics and Control (iREP) - VIII (iREP), 2010 iREP Symposium
Conference_Location :
Rio de Janeiro
Print_ISBN :
978-1-4244-7466-0
Electronic_ISBN :
978-1-4244-7465-3
Type :
conf
DOI :
10.1109/IREP.2010.5563272
Filename :
5563272
Link To Document :
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