CHIH-WEN LIUTsay, S.-S.S.-S.TsayWang, Y.-J.Y.-J.WangSu, M.-C.M.-C.Su2018-09-102018-09-10199903787796http://www.scopus.com/inward/record.url?eid=2-s2.0-0033098762&partnerID=MN8TOARShttp://scholars.lib.ntu.edu.tw/handle/123456789/348569https://www.scopus.com/inward/record.uri?eid=2-s2.0-0033098762&doi=10.1016%2fs0378-7796%2898%2900104-7&partnerID=40&md5=a2dd0f8d4f5695d323584c28af85ecbdWith new systems capable of making synchronized phasor measurements there are possibilities for real-time assessment of the stability of a transient swing in power systems. In the future, on-line control will be necessary as operating points are pushed closer toward the margin and fast reaction time becomes critical to the survival of the system. In this paper we develop a novel class of fuzzy hyperrectangular composite neural networks which utilize real-time phasor angle measurements to provide fast transient stability prediction for use with high-speed control. From simulation tests on a sample power system, it reveals that the proposed tool can yield a highly successful prediction rate in real-time.Fuzzy hyperrectangular composite neural network (FHRCNN); Phasor measurement unit (PMU); Real-time transient stability predictionComputer simulation; Fuzzy control; Neural networks; Speed control; Transients; Synchronized phasor measurements; Electric power systemsjournal article2-s2.0-0033098762