Sustainable energy solutions for rural electrification in a low-income community
Bibliographic record
Abstract
Addressing the simultaneous provision of electricity, heat, and water to rural areas is a pervasive global challenge. This study focuses on optimizing a poly-generation hybrid system that integrates PV, wind turbine, Combined Heat and Power (CHP) unit, battery, and brackish water reverse osmosis desalination, designed for warm climates, to meet the essential energy needs of Sar Goli village and a health clinic in Khuzestan province, Iran. Unlike previous studies, this research conducts sensitivity analyses considering diverse economic and climate conditions, evaluating the grid breakeven distance, environmental impact, and technical performance. The proposed 51.2 kW PV/10 kW WT/10 kW CHP/96 kWh BT/23.8 kW CNV system with reverse osmosis desalination demonstrates a cost of electricity (COE) and net present cost (NPC) of $0.161/kWh and $107,203, respectively. The study highlights that increased solar irradiation and wind speed contribute to cost efficiencies in renewable energy, resulting in lower NPC and COE values. However, rising diesel prices pose economic challenges for diesel-dependent systems, emphasizing the importance of strategic planning for resilient energy solutions. Additionally, improving boiler efficiency significantly reduces fuel consumption and CO2 emissions, emphasizing the interconnected nature of thermal load levels and environmental impact, guiding the path toward enhanced sustainability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".