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
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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 CO 2 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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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it