Evidence map›Paper›PMID 40629005›Full record

ArticleScientific reports2025

Enhancing MPPT optimization with hybrid predictive control and adaptive P&O for better efficiency and power quality in PV systems.

Benabdallah Naima, Belabbas Belkacem, Tahri Ahmed, Habib Benbouhenni, Bouddou Riyadh, Heroual Samira, Zaidi Sarra, Z M S Elbarbary, Salman Arafath Mohammed

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Benabdallah NaimaDepartment of Electrical Engineering, L2GEGI Laboratory, University of Tiaret, Tiaret, Algeria.
Belabbas BelkacemDepartment of Electrical Engineering, L2GEGI Laboratory, University of Tiaret, Tiaret, Algeria.
Tahri AhmedDepartment of Electrical Engineering, L2GEGI Laboratory, University of Tiaret, Tiaret, Algeria.
Habib BenbouhenniLaboratoire LAAS, Ecole Nationale Polytechnique d'Oran, EL M'naouer, Bp 1523, Oran, Algeria. habib.benbouhenni@enp-oran.dz.
Bouddou RiyadhDepartment of Electrical Engineering, Institute of Technology, University Centre of Naama, Naama, 45000, Algeria.
Heroual SamiraDepartment of Electrical Engineering, L2GEGI Laboratory, University of Tiaret, Tiaret, Algeria.
Zaidi SarraLaboratoire LAAS, Ecole Nationale Polytechnique d'Oran, EL M'naouer, Bp 1523, Oran, Algeria.
Z M S ElbarbaryDepartment of Electrical Engineering, College of Engineering, King Khalid University, KSA, P.O. Box 394, Abha, 61421, Saudi Arabia.
Salman Arafath MohammedDepartment of Electrical Engineering, College of Engineering, King Khalid University, KSA, P.O. Box 394, Abha, 61421, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, there has been a focus on renewable energy sources such as solar power. These grid-connected systems play a significant role in meeting energy demand and mitigating global warming. Despite these numerous benefits, the stability and quality of power are the main drawbacks facing these energy systems. Boost converters are used to maximize the power output of the photovoltaic system and power the load. The maximum power point tracking (MPPT) strategy based on the perturb and observe (P&O) algorithm is often used to control the inverter. This strategy yields unsatisfactory results in terms of operational performance and durability. This paper presents a new MPPT strategy for a photovoltaic inverter to improve power quality, stability, and dynamic performance. This new strategy is based on combining modified finite control set model predictive control (MFCS-MPC) with an adaptive P&O algorithm. This proposed strategy differs from the conventional strategy and some existing strategies in terms of robustness, operational performance, and dynamic response. MATLAB/Simulink was used to build and validate a comprehensive mathematical model of the studied system. The effectiveness, efficiency, and performance were studied under different operating conditions. The results show that using the designed MPPT approach achieves a total harmonic distortion of 1.22%, significantly outperforming the conventional P&O algorithm (6%) and complying with IEEE-519 standards. Also, using this designed MPPT approach improves tracking response time by an estimated 35% and reduces overshoot by 28%, ensuring stability under rapid changes in radiation. Furthermore, the new weighted cost function in MFCS-MPC reduces switching losses by 15% while maintaining harmonic suppression. These results highlight the effectiveness of the proposed MPPT approach and its ability to improve system properties compared to the conventional MPPT approach, making it a reliable solution for other energy applications such as wind energy and electric vehicles.

Indexed as

Maximum power point trackingModified finite control set model predictive controlPerturb and observe algorithmPhotovoltaic systemTotal harmonic distortion

Identifiers

PMID40629005
PMCPMC12238332

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.