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Record W7125513783 · doi:10.18280/jesa.581217

Ensuring MPPT Operability in BLDC Solar Pumping Systems: The Critical Role of PV Array Voltage Configuration – An Experimental Study

2025· article· W7125513783 on OpenAlexvenueno aff
Noureddine Benbaha, Abdelhak Bouchakour, Hachemi Ammar, Seif Eddine Boukebbous

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2025
Typearticle
Language
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPhotovoltaic systemOperabilityMaximum power point trackingVoltagePower (physics)Solar energy

Abstract

fetched live from OpenAlex

This study presents an experimental assessment of the influence of photovoltaic (PV) array voltage configuration on the performance of a 2.2 kW brushless DC (BLDC) solar water pumping system operating under real Saharan climatic conditions in Ghardaia, Algeria.Two PV array topologies, 8S 1P (245.6 V) and 4S 2P (122.8V), were evaluated at three total manometric heads (1 m, 15 m, and 25 m) using a commercial Jntech inverter featuring a maximum power point tracking (MPPT) operating window of 200-400 V.The 8S 1P configuration consistently maintained the PV voltage above the 200 V threshold, enabling uninterrupted MPPT functionality and achieving system efficiencies of 39-45% along with daily water yields of 30-60 m .Conversely, the 4S 2P configuration operated mainly below 200 V (110-135 V), which disabled the MPPT algorithm and forced operation in a fixed-duty-cycle bypass mode, resulting in markedly reduced system efficiencies (8-14%) and water production losses of 60-85%.These findings demonstrate that PV array voltage adequacy rather than array power rating alone is the key determinant of reliable and efficient solar pumping system performance.The results provide practical design guidance for off-grid pumping applications in arid and high-irradiance environments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.303
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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