
Validation of photovoltaics powered UPQC using ANFIS controller in a standard microgrid test environment
Author(s) -
S Sumana,
R Dhanalakshmi,
Sriram Kumar Dhamodharan
Publication year - 2022
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijece.v12i1.pp92-101
Subject(s) - microgrid , computer science , renewable energy , adaptive neuro fuzzy inference system , voltage , voltage sag , controller (irrigation) , automotive engineering , reliability engineering , power quality , engineering , electrical engineering , fuzzy logic , fuzzy control system , artificial intelligence , agronomy , biology
The power quality improvement becomes one of the important tasks while using microgrid as main power supply. Because the microgrid is combination of renewable energy resources. The renewable energy resources are intermittent in power supply and at the peak loading condition it has to supply the required power. So, the power quality problems may increase in that time. Out of all power quality issues the voltage drop and harmonic distortion is considered as the most serious one. In recent years unified power quality conditioner (UPQC) is emerged as most promising device which compensates both utility as well as customer side power quality disturbances in effective way. The compensating potentiality used in the UPQC is limited by the use of DC link voltage regulation and the conventional proportional integral (PI) controller. In this paper the compensating potentiality of the UPQC device is controlled by an adaptive neuro fuzzy inference system (ANFIS) control and it is powered from the available photovoltaics (PV) power generation. The effect of adding an intelligent UPQC is tested in the standard IEEE-14bus environment. MATLAB 2017b is used here for testing and plotting the simulation results.