Comparison between Seven MPPT Techniques Implemented in a Buck Converter

Author(s): Lahcen El Mentaly*, Abdellah Amghar, Hassan Sahsah.

Journal Name: Recent Advances in Electrical & Electronic Engineering
Formerly Recent Patents on Electrical & Electronic Engineering

Volume 12 , Issue 6 , 2019

Become EABM
Become Reviewer

Abstract:

Background: The solar field on our planet is inexhaustible, which favors the use of photovoltaic electricity which generates no nuisance: no greenhouse gases, no waste.

Methods: It is a high value-added energy that is produced directly at the place of consumption through photovoltaic (PV) solar panels. Notwithstanding these advantages, the maximum power depends strongly on solar irradiation and temperature, which means that a Maximum Power Point Tracking (MPPT) controller must be inserted between the PV panel and the load in order to follow the Maximum Power Point (MPP) continuously and in real time. In this work, MPP’s behavior was simulated at different temperatures and solar irradiations using seven techniques which identify the MPP by different methods.

Results: The novelty of this work is that the seven MPPT methods were compared according to a very selective criterion which is the MPPT efficiency as well as a purely digital duty cycle control without using the PI controller. The simulation under the PSIM software shows that the FLC, TP, FSCC, TG, HC and IC methods have almost the same efficiency of 99%, whereas the FOCV method had a low efficiency of 96%.

Conclusion: This makes it possible to conclude that the best methods are FLC, HC and IC because they use fewer sensors compared to the rest.

Keywords: MPPT, buck converter, photovoltaic module, hill climbing, incremental conductance, fuzzy logic control, opencircuit voltage method, short-circuit current method, Temperature Gradient (TG), Temperature Parametric (TP).

Rights & PermissionsPrintExport Cite as

Article Details

VOLUME: 12
ISSUE: 6
Year: 2019
Page: [476 - 486]
Pages: 11
DOI: 10.2174/2352096511666180705113647
Price: $95