Reliability assessment of a solar powered center pivot irrigation system
Bibliographic record
Abstract
Photovoltaic (PV) technology, used for generating power from solar radiation, has great potential for adoption in irrigated agriculture since both the energy produced and required (irrigation demand) strongly depend on solar radiation. However, successful application of this technology depends on a system design approach that considers how the irrigation system specifications vary with climate, crop type, soil water holding characteristics, and the irrigation management strategy. The objective of this study was to develop a model for assessing the reliability of a PV-powered center pivot irrigation system by combining sub-models for the power production, energy storage, and the required irrigation-related load, while considering variable operating and meteorological conditions. Given the required input variables, the model determines the reliability of the PV system by analyzing the condition for which both power produced by the generator and stored in the batteries are sufficient to fulfil the irrigation demands. The model was validated by comparing the model results to field measurements of a small (1.4 ha) solar-powered center pivot irrigation system, located at Outlook, Saskatchewan, Canada. The results showed an excellent agreement between the simulated system and the field data. The model is intended to be applied as a design tool to determine the required size of the PV system to achieve the desired reliability of the overall irrigation system.
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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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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".