FRANÇAIS
A showcase of ÉTS researchers’ publications and other contributions
SEARCH

Improved Restricted Control Set Model Predictive Control (iRCS-MPC) based maximum power point tracking of photovoltaic module

Downloads

Downloads per month over past year

Hussain, A., Sher, H. A., Murtaza, A. F. et Al-Haddad, K.. 2019. « Improved Restricted Control Set Model Predictive Control (iRCS-MPC) based maximum power point tracking of photovoltaic module ». IEEE Access, vol. 7. pp. 149422-149432.
Compte des citations dans Scopus : 1.

[img]
Preview
PDF
Al Haddad K 2019 19868.pdf - Published Version
Use licence: Creative Commons CC BY.

Download (5MB) | Preview

Abstract

This paper presents a robust two stage maximum power point tracking (MPPT) system of the photovoltaic (PV) module using an improved restricted control set model predictive control (iRCS-MPC) technique. The suggested work is improved in two aspects; a revision in conventional P&O algorithm is made by employing three distinct step sizes for different conditions, and an improvement in conventional MPC algorithm. The improved MPC algorithm is based on the single step prediction horizon that provides less computational load and swift tracking of maximum power point (MPP) by applying the control pulses directly to the converter switch. The computer aided experimental results for various environmental scenarios revealed that compared with the conventional method (conventional P&O + MPC), for the PV power and inductor current, the undershoot and overshoot is decreased to 68% and 35% respectively under stiff environmental conditions. In addition, the settling time needed to reach a stable state is significantly reduced in the proposed system. The viability of the solution suggested is verified in MATLAB/Simulink and by hardware experimentation.

Item Type: Peer reviewed article published in a journal
Professor:
Professor
Al Haddad, Kamal
Affiliation: Génie électrique
Date Deposited: 03 Dec 2019 20:30
Last Modified: 13 Dec 2019 16:17
URI: https://espace2.etsmtl.ca/id/eprint/19868

Actions (login required)

View Item View Item