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Record W4416028818 · doi:10.24018/ejece.2025.9.6.759

Dynamic Modeling and Simulation of a Solar-Powered Water Pumping System for Irrigation in Kufri, Pakistan

2025· article· W4416028818 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Electrical Engineering and Computer Science · 2025
Typearticle
Language
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsWater pumpingPhotovoltaic systemIrrigationInduction motorMaximum power point trackingBattery (electricity)InverterPower (physics)System dynamics

Abstract

fetched live from OpenAlex

This paper presents the dynamic simulation and performance evaluation of a solar-powered water pumping system designed for irrigation in Kufri, Khushab, Pakistan. The design is based on the previously developed in HOMER optimized model and extended into MATLAB/Simulink to analyze real-time behavior. The paper represents a design with an 8.75 kW photovoltaic array, a 48 V storage battery bank, a 7.11 kW inverter, and a 7.5 HP submersible induction motor pump. To assess its performance, the model integrates a Maximum Power Point Tracking (MPPT) control scheme, a DC–DC buck converter, a three-phase DC-AC inverter, and a step-up transformer. Simulation outcomes covering PV response curves, inverter voltage output, motor operational behavior, and battery charging and discharging profiles demonstrate steady performance, consistent irrigation of about 137–140 m3 per day, and strong tolerance to changes in solar irradiance. These findings verify that the previous study HOMER-optimized configuration is practically achievable and represents a sustainable approach for irrigation needs in rural agricultural areas.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.803
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.232
Teacher spread0.225 · 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