Open AccessFractional order Sprott chaos synchronisation‐based real‐time extension power quality detection method
Author(s) -
Yau HerTerng,
Wang ChengChi,
Hsieh ChinTsung,
Wu ShangYi
Publication year - 2015
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2015.0500
Subject(s) - computer science , harmonics , chaotic , voltage sag , power (physics) , electric power system , control theory (sociology) , integer (computer science) , chaos (operating system) , synchronization (alternating current) , real time computing , signal (programming language) , voltage , artificial intelligence , engineering , telecommunications , physics , control (management) , computer security , quantum mechanics , electrical engineering , programming language , channel (broadcasting)
It is known that real‐time power quality monitoring is usually rather difficult to achieve due to the requirement of expensive equipments and necessary of more signals to be captured. To solve this problem, this study combines fractional order Sprott chaos synchronisation system with extension theory to detect power signal disturbance including voltage swell, sag, interruption, and harmonics for real‐time power quality monitoring. The use of fractional order chaotic systems can significantly improve the situations of misjudgement due to the dynamic error is too large by using general integer order chaotic systems. Otherwise, the three‐dimensional (3D) Sprott error dynamics can be reduced to 2D error system. It will become easier and cheaper to implement this scheme in the portable device. The results of numerical simulation show that the detection accuracy rate is 100% and it is better than the methods in previous studies. It should be able to get a very high diagnostic accuracy if this method can be applied to the actual power system.