Application of two-stage ADALINE for estimation of synchrophasor

Author(s): Cheng-I Chena*, Yeong-Chin Chenb, Chao-Nan Chenb, Chien-Kai Lanb
National Central University, No. 300, Jhongda Rd., Jhongli City, Taoyuan County 32001, Taiwan
Asia University, No. 500, Lioufeng Rd., Wufeng, Taichung 41354, Taiwan
International Journal of Smart Grid and Clean Energy, vol. 2, no. 3, October 2013: pp. 316–321
ISSN: 2315-4462
Digital Object Identifier: 10.12720/sgce.2.3.316-321


Abstract: With the development of smart grid, the accurate estimation of phasor measurement is increasingly significant to help achieve the reliable transmission and distribution of power system. However, the power system frequency may deviate from its nominal value and lead to estimation errors for the most traditional approaches. To perform the accurate synchrophasor measurement, a technique based on adaptive linear neural network (ADALINE) is applied. With the high frequency resolution of autoregressive model, the variation of power system frequency can be effectively extracted. Through the testing results corresponding to different power quality disturbances, the total vector errors of several uncertainty examinations for synchrophasor measurement in IEEE Std. C37.118.1-2011 can be maintained in the permissible range.

Keywords: Adaptive linear neural network, synchrophasor, autoregressive model, total vector error, power quality disturbance

Full Paper.pdf
Copyright © 2022 International Journal of Smart Grid and Clean Energy, All Rights Reserved