Open AccessPerformance of Interline Unified Power Quality Conditioner IUPQC With PI, Fuzzy and ANFIS Controllers
Author(s) -
A Navya,
A Panduranga Rao,
Lan Rao
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.c5497.029320
Subject(s) - adaptive neuro fuzzy inference system , control theory (sociology) , control engineering , fuzzy logic , pid controller , controller (irrigation) , matlab , voltage , computer science , power (physics) , engineering , compensation (psychology) , fuzzy control system , control (management) , artificial intelligence , electrical engineering , temperature control , agronomy , physics , quantum mechanics , biology , operating system , psychology , psychoanalysis
Several artificial intelligent control schemes are highly used in several applications, in that ANFIS controller has been greatly recognized due to enhanced performance over the classical PI and Fuzzy controllers. At present the multi-feeder power distribution system is deteriorated with continuity of supply and poor power quality standards. In this multi-feeder distribution system, it is a regular consumer related issue which is acquired due to malfunctioning of massive non-linear loads. These loads create the voltage or current imperfections on distribution networks which disrupts the power quality of distribution system. An efficient and reliable active compensation scheme is used for attaining enhanced power quality features at PCC of multi-feeder distribution system with effective control functions. The Multi-Feeder Unified Power Quality Compensator (MF-UPQC) is optimal choice for attaining enhanced power quality features and it is a combined shunt or series compensator driven by common DC-link. This paper recommends the Adaptive Neuro-Fuzzy Intelligent Controller (ANFIS) based prediction technique for generation of optimal switching states to enhance performance of proposed MF-UPQC to compensate all voltage-current PQ imperfections. The performance of proposed MF-UPQC is verified by classical PI, Fuzzy and proposed ANFIS control functions by using MATLAB/SIMULINK tool and results are conferred with proper comparisons.