Optimized Control of a Hybrid Water Pumping System Integrated with Solar Photovoltaic and Battery Storage: Towards Sustainable and Green Water-Power Supply
Bibliographic record
Abstract
This article presents the modeling and optimization control of a hybrid water pumping system utilizing a brushless DC motor. The system incorporates battery storage and a solar photovoltaic array to achieve efficient water pumping. The solar array serves as the primary power source, supplying energy to the water pump for full-volume water surrender. During unfavorable weather conditions or when the photovoltaic array is unable to meet the power demands of the water pump, the battery discharges only at night or during inadequate solar conditions. Additionally, the photovoltaic array can charge the battery on its own when water distribution is not necessary, negating the need for external power sources. A bi-directional charge control mechanism is employed to facilitate automatic switching between the operating modes of the battery, utilizing a buck-boost DC–DC converter. The study incorporates a control system with loops for battery control and DC voltage control within the bidirectional converter. The water cycle algorithm adjusts four control parameters by minimizing an objective function based on tracking errors. The water cycle optimization is compared to other methods based on overshoot and settling time values to evaluate its performance, showcasing its effectiveness in analyzing the results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".