Design and Experimental Implementation of a Hysteresis Algorithm to Optimize the Maximum Power Point Extracted from a Photovoltaic System

Nubia Ilia Ponce de León Puig, Leonardo Acho and José Rodellar
Additional contact information
Nubia Ilia Ponce de León Puig: Department of Mathematics, Escola d’Enginyeria de Barcelona Est-EEBE, Universitat Politècnica de Catalunya-BarcelonaTech (UPC), 08034 Barcelona, Spain
Leonardo Acho: Department of Mathematics, Escola d’Enginyeria de Barcelona Est-EEBE, Universitat Politècnica de Catalunya-BarcelonaTech (UPC), 08034 Barcelona, Spain
José Rodellar: Department of Mathematics, Escola d’Enginyeria de Barcelona Est-EEBE, Universitat Politècnica de Catalunya-BarcelonaTech (UPC), 08034 Barcelona, Spain

Energies, 2018, vol. 11, issue 7, 1-24

Abstract: In the several last years, numerous Maximum Power Point Tracking (MPPT) methods for photovoltaic (PV) systems have been proposed. An MPPT strategy is necessary to ensure the maximum power efficiency provided to the load from a PV module that is subject to external environmental perturbations such as radiance, temperature and partial shading. In this paper, a new MPPT technique is presented. Our approach has the novelty that it is a MPPT algorithm with a dynamic hysteresis model incorporated. One of the most cited Maximum Power Point Tracking methods is the Perturb and Observer algorithm since it is easily implemented. A comparison between the approach presented in this paper and the known Perturb and Observer method is evaluated. Moreover, a new PV-system platform was properly designed by employing low cost electronics, which may serve as an academical platform for further research and developments. This platform is used to show that the proposed algorithm is more efficient than the standard Perturb and Observer method.

Keywords: maximum power point tracking; photovoltaic system; hysteresis; modeling; electronic design (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/7/1866/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/7/1866/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:7:p:1866-:d:158414

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().