Optimal sizing and techno-economic analysis of a renewable power system for a remote oil well
Bibliographic record
Abstract
There is a growing interest in the deployment of off-grid renewable energy, especially for remote oil and gas facilities. This work is a novel attempt to optimally size a renewable energy system to power artificial lift for an oil well. It proposes a low-cost alternative to abandonment and decommissioning of old wells. Sucker-rod pump artificial lift simulators (QRodTM and PROSPERTM) are deployed to estimate the energy requirement of a well, with both intermittent and continuous pumping considerations. Simulation and optimization are performed using HOMER optimizerTM, which produces different system configurations and presents the possible configurations in order of increasing system costs. Based on economic and technical merits, continuous pumping using a hybrid renewable energy system consisting of a solar, wind and battery storage is chosen as the most feasible solution with 0 kWh/yr of unmet load, a capacity storage of 0.56 kWh/yr, net present cost of $ 145,150.50, levelized cost of energy of $ 0.51/kWh and an operating cost of $3,056.04/yr. The optimal configuration is finally examined to determine its sensitivity to variation in daily solar radiation and average wind speed. It is demonstrated to be the most preferred system design, even at the least daily average solar radiation.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".