Dynamic Modeling and Simulation of a Solar-Powered Water Pumping System for Irrigation in Kufri, Pakistan
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".