Evidence map›Paper›PMID 37922271›Full record

ArticlePloS one2023

A new adaptive MPPT technique using an improved INC algorithm supported by fuzzy self-tuning controller for a grid-linked photovoltaic system.

Nagwa F Ibrahim, Mohamed Metwally Mahmoud, Hashim Alnami, Daniel Eutyche Mbadjoun Wapet, Sid Ahmed El Mehdi Ardjoun, Mohamed I Mosaad, Ammar M Hassan, H Abdelfattah

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

8 authors.

Nagwa F IbrahimElectrical Department, Faculty of Technology and Education, Suez University, Suez, Egypt.ORCID 0000-0003-3978-7245
Mohamed Metwally MahmoudDepartment of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan, Egypt.ORCID 0000-0002-2460-1850
Hashim AlnamiElectrical Engineering Department, Jazan University, Jazan, KSA.
Daniel Eutyche Mbadjoun WapetNational Advanced School of Engineering, Université de Yaoundé I, Yaoundé, Cameroon.ORCID 0009-0004-3065-9188
Sid Ahmed El Mehdi ArdjounIRECOM Laboratory, Faculty of Electrical Engineering, Djillali Liabes University, Sidi Bel-Abbes, Algeria.
Mohamed I MosaadElectrical & Electronics Engineering Technology Department, Yanbu Industrial College (YIC), Royal Commission Yanbu Colleges & Institutes, Yanbu, Saudi Arabia.
Ammar M HassanArab Academy for Science, Technology and Maritime Transport, South Valley Branch, Aswan, Egypt.
H AbdelfattahElectrical Department, Faculty of Technology and Education, Suez University, Suez, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Solar energy, a prominent renewable resource, relies on photovoltaic systems (PVS) to capture energy efficiently. The challenge lies in maximizing power generation, which fluctuates due to changing environmental conditions like irradiance and temperature. Maximum Power Point Tracking (MPPT) techniques have been developed to optimize PVS output. Among these, the incremental conductance (INC) method is widely recognized. However, adapting INC to varying environmental conditions remains a challenge. This study introduces an innovative approach to adaptive MPPT for grid-connected PVS, enhancing classical INC by integrating a PID controller updated through a fuzzy self-tuning controller (INC-FST). INC-FST dynamically regulates the boost converter signal, connecting the PVS's DC output to the grid-connected inverter. A comprehensive evaluation, comparing the proposed adaptive MPPT technique (INC-FST) with conventional MPPT methods such as INC, Perturb & Observe (P&O), and INC Fuzzy Logic (INC-FL), was conducted. Metrics assessed include current, voltage, efficiency, power, and DC bus voltage under different climate scenarios. The proposed MPPT-INC-FST algorithm demonstrated superior efficiency, achieving 99.80%, 99.76%, and 99.73% for three distinct climate scenarios. Furthermore, the comparative analysis highlighted its precision in terms of control indices, minimizing overshoot, reducing rise time, and maximizing PVS power output.

Indexed as

Electric Power SuppliesModels, TheoreticalAlgorithmsComputer SimulationFuzzy Logic

Identifiers

PMID37922271
PMCPMC10624298

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.