Abstract
AbstractApplication of typical Mamdani fuzzy inference system (MFIS) in power system protection has become a common artifact nowadays. The proposed articles on fuzzy logic-based protection initially designed the controller using typical MFIS. The related works mostly followed centroid defuzzification method. It is observed that the defuzzification method generally ensures multiple outputs. This output generally introduces lagging in detecting faults most of the time. It also delays the overall system by extending the coordination time as well. In this paper, a new FIS is discussed in terms of intelligent relaying benefits. Inverted pendulum model is considered to explain the novelty of granular differentiability. Initially, the proposed method is faster as due to its single solution-based features. This granular differentiability is considered as defuzzification method and incorporated into a new kind of fuzzy controller. The controller deals with a novel fuzzy inference system usually known as fractional fuzzy inference system. This fractional fuzzy inference system is found to respond 100% accurate and faster indeed as compared to Mamdani fuzzy inference system and reported.KeywordsFaultGranular differentiabilityMembership functionProtectionRestrikingTRIP
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
