Performance Analysis of Different Optimization Algorithms for MPPT Control Techniques under Complex Partial Shading Conditions in PV Systems

Nihat Pamuk ()
Additional contact information
Nihat Pamuk: Department of Electrical Electronics Engineering, Zonguldak Bulent Ecevit University, Zonguldak 67100, Turkey

Energies, 2023, vol. 16, issue 8, 1-25

Abstract: Classic algorithms show high performance in tracking the maximum power point (MPP) of photovoltaic (PV) panels under uniform irradiance and temperature conditions. However, when partial or complex partial shading conditions occur, they fail in capturing the global maximum power point (GMPP) and are trapped in one of the local maximum power points (LMPPs) leading to a loss in power. On the other hand, intelligent algorithms inspired by nature show successful performance in GMPP tracking. In this study, an MPPT system was set up in MATLAB/Simulink software consisting of six groups of serially connected PV panels, a DC-DC boost converter, and load. Using this system, the cuckoo search (CS) algorithm, the modified incremental conductivity (MIC) algorithm, the particle swarm optimization (PSO) algorithm, and the grey wolf optimization (GWO) algorithm were compared in terms of productivity, convergence speed, efficiency, and oscillation under complex shading conditions. The results showed that the GWO algorithm showed superior performance compared to the other algorithms under complex shading conditions. It was observed that GWO did not oscillate during GMPP tracking with an average convergence speed of 0.22 s and a tracking efficiency of 99%. All these evaluations show that GWO is a very fast, highly accurate, efficient, and stable MPPT method under complex partial shading conditions.

Keywords: photovoltaic systems; complex partial shading; MPPT; CS; GWO; MIC; PSO (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: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/8/3358/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/8/3358/ (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:16:y:2023:i:8:p:3358-:d:1120501

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 ().