Optimally-Sized Design of a Wind/Diesel/Fuel Cell Hybrid System for a Remote Community
Bibliographic record
Abstract
Remote communities, characterized by no connection to the main power grid, traditionally get their power from diesel generators. Long geographical distances and lack of suitable roads make the fuel transportation difficult and costly, increasing the final cost of electricity. A microgrid using renewable energy as the main source can serve as a viable solution for this problem with considerable economical and environmental benefits. The focus of this research is to develop a microgrid for a remote community in northern Ontario (Canada) that combines wind, as a renewable source of energy, and a hydrogen-based energy storage system, with the goal of meeting the demand, while minimizing the cost of energy and adverse effect on the environment. The existing diesel generators remain in the system, but their use is minimized. \n \nThe microgrid system studied in this research uses a wind turbine to generate electricity, an electrolyser to absorb the excess power from the wind source, a hydrogen tank to store the hydrogen generated by the electrolyser, a fuel cell to supply the demand when the wind resource is not adequate, and a diesel generator as a backup power. \n \n Two scenarios for unit-sizing are defined and their pros. and cons. are discussed. The economic evaluation of scenarios is performed and a cost function for the system is defined. The optimization problem thus formulated is solved by solvers in GAMS. The inputs are wind profile of the area, load profile of the community, existing sources of energy in the area, operating voltage of the grid, and sale price of electricity in the area. The outputs are the size of the fuel cell and electrolyser units that should be used in the microgrid, the capital and running costs of each system, the payback period of the system, and cost of generated electricity. Following this, the best option for the microgrid structure and component sizes for the target community is determined. \n \nFinally, a MATLAB-based dynamic simulation platform for the system under study with similar load/wind profile and sizing obtained in optimization problem is developed and the dynamic behaviour of microgrid at different cases is studied.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".