Effect of Temperature Coefficient Evaluation on Optimal Analysis of Hybrid Energy Systems for a Mall in KwaZulu-Natal, South Africa
Bibliographic record
Abstract
Suitable technical sizing of a standalone off-grid power system impacts its economic and technical analysis. This research examines the effect of the temperature coefficient to determine the optimal analysis of a standalone off-grid power system considering the case of a standard mall in KwaZulu-Natal, South Africa, during the crucial 2021 wave of load shedding. Scenarios without temperature coefficients and vice versa were also analyzed for comparison purposes. The system was modeled in a MATLAB environment for optimum component configuration. The analyses showed that the presence of a temperature coefficient results in higher operating costs for the fossil fuel generator because of its increased operation hours, thereby consuming more fossil fuel. It was also discovered that although the capital investment of the hybrid energy system (HES) is higher than that of the fossil-fuel generator alone, its greenhouse gas emission is far lower, producing clean, safe, and sustainable energy.
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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 | 0.015 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".