Techno‐economic feasibility study of autonomous hybrid wind and solar power systems for rural areas in <scp>I</scp>ran, A case study in <scp>M</scp>oheydar village
Bibliographic record
Abstract
In this research, a feasibility study of using a small wind turbine as an integrated system with a solar photovoltaic system and a diesel generator was performed using the HOMER® optimization model. For this purpose three main scenarios have been taken into account. In the first two scenarios the diesel price was considered 0.8 $/L (Scenario 1) and 1.5 $/L (Scenario 2) and no limits were assumed for emissions of diesel generator. The most efficient system in the first scenario consists of one wind turbine (15 kW), a 75 kW generator, 35 batteries, and a 15 kW converter with renewable fraction of 53%. However in the second scenario, 7 kW photovoltaic array was added to the designed optimal hybrid system and thus the renewable fraction was increased to 71%. In the third scenario the limits were specified for the different pollutants using the CAP (Ontario Clean Air Program) standard. It was revealed that the optimal configuration which contains a 75 kW diesel generator, 21 kW photovoltaic array, 75 kW wind turbines, 50 batteries, and a 20 kW converter would be the most economically feasible. Emission analysis revealed that among all of the designed hybrid systems, highest level of CO2 emissions was observed for a stand‐alone diesel system with value of 115,436 kg/yr and the lowest level was observed for the hybrid system in the third scenario with value of 991 kg/yr. Additionally it was proved that the third scenario would be the best option for connecting the system to the grid. © 2015 American Institute of Chemical Engineers Environ Prog, 34: 1521–1527, 2015
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".