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Design and modelling of an AI governed type-2 Fuzzy tilt control strategy for AGC of a multi-source power grid in constraint to optimal dispatch

Authors :
Ashok Kumar Mohapatra
Srikanta Mohapatra
Amruta Pattnaik
Prakash Chandra Sahu
Source :
e-Prime: Advances in Electrical Engineering, Electronics and Energy, Vol 7, Iss , Pp 100487- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

The robust design and application of a novel type-2 fuzzy tilt controller (Type2-FTC) has been well demonstrated in this manuscript. This controller is anticipated to build automatic generation control (AGC) of a multi-area hybrid power system in concern to the optimal power generation scheduling. The combined action of AGC and optimal scheduling of a power system is referred as economic AGC or commonly ELD-AGC. At the initial stage of the analysis, the concept of only AGC has been discussed through various robust approaches. Then the extensive study on ELD-AGC of the proposed power system has been progressed under various controller actions. Further, the proposed Type2-FTC controller is designed ideally with employing an innovative quassi-opposition path finder algorithm (QO-PFA) in various operating conditions. The effectiveness and the viability of the proposed Type2-FTC controller has been verified over type-I fuzzy PID and conventional PID controllers for AGC as well as ELD-AGC of the multi area power system. In controller comparison study, it has been revealed that proposed Type2-FTC is a potential candidate to improve frequency stability of the system. Further, the analysis over technique study justifies supremacy of the suggested QO-FPA algorithm over standard PFA and PSO algorithms for optimal designing all implemented controllers.

Details

Language :
English
ISSN :
27726711
Volume :
7
Issue :
100487-
Database :
Directory of Open Access Journals
Journal :
e-Prime: Advances in Electrical Engineering, Electronics and Energy
Publication Type :
Academic Journal
Accession number :
edsdoj.1fe41dd21f1433f8d67288a50974805
Document Type :
article
Full Text :
https://doi.org/10.1016/j.prime.2024.100487