Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Fuzzy logic gain‐tuned adaptive second‐order GI‐based multi‐objective control for reliable operation of grid‐interfaced photovoltaic system

Vedantham, Srinivas, Kumar, Shailendra, Singh, Bhim and Mishra, Sukumar 2018. Fuzzy logic gain‐tuned adaptive second‐order GI‐based multi‐objective control for reliable operation of grid‐interfaced photovoltaic system. IET Generation, Transmission and Distribution 12 (5) , pp. 1153-1163. 10.1049/iet-gtd.2017.0958

[thumbnail of iet-gtd.2017.0958.pdf] PDF - Published Version
Available under License Creative Commons Attribution.

Download (8MB)

Abstract

This study presents the fuzzy logic integrator gain‐tuned improved second‐order generalized integrator (GI) for a double‐stage grid‐interfaced photovoltaic (PV) system. The proposed system includes the functionalities of feeding active power to the grid, power factor correction, grid currents balancing and system isolation under grid side faults. Moreover, the smooth system operation is ensured under weak distribution grids where grid voltage is subject to huge diversions. Furthermore, automatic protection scheme for the system under grid‐side faults is also established with the proposed algorithm for increased reliability. The fuzzy‐tuned GI provides advantages of efficient and effective extraction of load current fundamental component under steady‐state and dynamic grid conditions. The non‐linear frequency error variation is compensated here using fuzzy logic‐based self‐tuning integrator gain of the controller. The controller is improved to mitigate the possible DC component in the load current. The neutral current in the loads is nullified by using a four wire system. The adaptive DC bus voltage helps to minimize the switching losses and prevents unexpected tripping of the PV inverter. The system is experimentally verified using a prototype built in the laboratory.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Institution of Engineering and Technology (IET)
ISSN: 1751-8687
Date of First Compliant Deposit: 1 April 2021
Date of Acceptance: 28 October 2017
Last Modified: 01 Apr 2021 14:45
URI: https://orca.cardiff.ac.uk/id/eprint/140246

Citation Data

Cited 12 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics