Dispatch techniques for Canadian remote communities with renewable sources
Bibliographic record
Abstract
The appropriate dispatch of Load Shifting Devices (LSD) and Renewable Energy Sources (RES) is still a challenging issue for the Remote Community (RC). This paper analyzes three techniques for the economic dispatch of a RC microgrid that implements RES and LSDs as in the case of Energy Storage Systems (ESS) to a diesel infrastructure. Two online or period-ahead techniques are compared to an offline mathematical formulation of a PV-ESS-Diesel system for an hourly-based annual simulation. A new online method, based on the average cost curve of a generator is introduced as it consists in a combination between the closed mathematical formulation of a classic offline technique and the online capabilities of a Knowledge-Based Expert System (KBES). An application of the three techniques over the same benchmark shows that by the introduction of a load shifting capability of approximately 25% of the peak, for all three methods the RC is able to save around 3% of the overall diesel consumption of a PV-Diesel Microgrid (MG).
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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) | 0.000 | 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".