The techno-economic and environmental aspects of a hybrid PV-diesel-battery power system for remote farm houses
Bibliographic record
Abstract
In this study, the solar radiation data of Balikesir in Turkey are analysed to assess the techno-economic viability and environmental performance of a hybrid Photovoltaic (PV)-diesel-battery system to meet the load requirements of a typical remote farm house. Several aspects of the system are studied through the Cost of Energy (CoE), the operational hours of diesel generator, unmet load, excess electricity generation, percentage of fuel savings, etc. The CoE for this kind of hybrid system is found to be 1.245 US$ /kWh. Simulations are performed for three cases (diesel only, PV-diesel and PV-diesel-battery). It is found that a diesel-only system produces 63 900 kWh of electricity and 69.7 tonnes of CO2, 13.0 kg of PM, 1.53 tonnes of NOx emissions per year. Using PV-diesel and PV-diesel-battery systems helps reduce the emissions for CO2 to 61.0 and 42.0 tonnes, for PM to 11.4 and 7.83 kg and for NOx to 1.34 and 0.92 tonnes, respectively. The diesel-only system is more economical if the fuel price remains below US$2/L. Otherwise, PV-diesel and PV-diesel-battery systems become more cost-effective. Also, the environmental impact improvement factor is found as 0.127 and 0.399 for CO2, 0.123 and 0.397 for PM and 0.124 and 0.398 for NOx for both PV-diesel and PV-diesel-battery systems, respectively.
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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) | 0.000 | 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) | 0.001 | 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".