A Review and New Problems Discovery of Four Simple Decentralized Maximum Power Point Tracking Algorithms—Perturb and Observe, Incremental Conductance, Golden Section Search, and Newton’s Quadratic Interpolation

Victor Andrean, Pei Cheng Chang and Kuo Lung Lian
Additional contact information
Victor Andrean: Department of Electrical Engineering, National Taiwan University of Science and Technology, 2F, EE, No. 43, Sec. 4, Keelung Rd, Taipei 106, Taiwan
Pei Cheng Chang: Department of Electrical Engineering, National Taiwan University of Science and Technology, 2F, EE, No. 43, Sec. 4, Keelung Rd, Taipei 106, Taiwan
Kuo Lung Lian: Department of Electrical Engineering, National Taiwan University of Science and Technology, 2F, EE, No. 43, Sec. 4, Keelung Rd, Taipei 106, Taiwan

Energies, 2018, vol. 11, issue 11, 1-25

Abstract: Maximum Power Point Tracking (MPPT) enables photovoltaic (PV) systems to extract as much solar energy as possible. Depending on which type of controller is used, PV systems can be classified as centralized MPPT (CMPPT) or decentralized MPPT (DMPPT). In substring-level systems, it is known that the energy yield of DMPPT can outweigh the power electronics cost. At the substring level, it is usually assumed that the PV curve exhibits a single peak, even under partial shading. Thus, the control algorithms for DMPPT are usually less complicated than those employed in CMPPT systems. This paper provides a comprehensive review of four simple DMPPT algorithms, which are perturb and observe (P&O), incremental conductance (INC), golden section search (GSS), and Newton’s quadratic interpolation (NQI). The comparison of these algorithms are done from the perspective of numerical analysis. Guidelines on how to set initial conditions and convergence criteria are thoroughly explained. This is of great interest to PV engineers when selecting algorithms for use in MPPT implementations. In addition, various problems that have never previously been identified before are highlighted and discussed. For instance, the problems of NQI trap is identified and methods on how to mitigate it are also discussed. All the algorithms are tested under various conditions including static, dynamic, and rapid changes of irradiance. Both simulation and experimental results indicate that P&O and INC are the best algorithms for DMPPT.

Keywords: decentralized maximum power point tracking; perturb and observe (P&O); incremental conductance (INC); golden section search (GSS); Newton’s quadratic interpolation (NQI) (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 (10)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/11/2966/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/11/2966/ (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:11:p:2966-:d:179651

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 ().