Optimal sizing, modeling, and design of a supervisory controller of a stand-alone hybrid energy system
Bibliographic record
Abstract
Microwave repeaters are one of the main energy consumers in the telecommunication industry. These repeaters are powered using diesel generators and batteries, particularly when they are located in remote areas. Diesel generators require a higher maintenance cost and for remote sites this cost will be more due inaccessibility and spare transportation to the added its operating cost. This thesis researches optimal sizing and compares a non-renewable energy system (existing system) and a renewable energy system (proposed system) for a remotely located telecommunication site in Mulligan, Labrador in Canada. The current system is operated using a diesel generator and batteries and the proposed system is expected to integrate a hybrid wind and solar energy system with the existing diesel generator and batteries. Hybrid Optimization Model for Electric Renewable (HOMER) software is used to obtain the most feasible configuration of a hybrid renewable energy system. Secondly, the proposed hybrid system is modeled in Matlab/Simulink and results are presented to demonstrate the system's performance. Finally, a real time supervisory controller has been designed and implemented for a small scale hybrid power system at Memorial University of Newfoundland. The overall reliability is guaranteed since there are two backup sources; battery bank and diesel generator. The results show the hybrid renewable energy system is cost effective. The proposed system significantly reduces the running time of the diesel generator and this helps to reduce the emission level. Moreover, it is expected that the proposed system will help the BellAliant Company to provide uninterrupted power for their sites in remote areas of Labrador.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".