Utilizing PV System for Auxiliary Energy Demand in Conventional Power Plant
Bibliographic record
Abstract
The purpose of this study is to investigate the utilization of PV feeding system for auxiliary energy demand in the conventional power plants. A 573 MW tri-fuel power plant in Jordan IPP3 the largest internal combustion engine (ICE) power plant in the world is the case study to evaluate the energy economy aspects of PV feeding system and its effects on the monthly payments for this energy. All relevant computations will be performed in order to end up with reasonable, feasible and applicable results. The auxiliary energy demand of this power plant while no operation is covered from the national transmission grid which results in around 48 MWh imported energy on daily basis taking in mind no operation case. Therefore, such PV system will have a noticeable impact over the productivity of the whole plant as well as raising the money spent for fuel upon the reduction of the heat rate. The PV system is sized to have a capacity of 2 MWp planned to be utilized during the day time. Considering the imported energy benefit, the corresponding pay-back period will through the 5th year where is expected to be accomplished during the 7th year when it comes to the heat rate improvement. The prominent fact to be mentioned here that the pay-back period upon either imported energy benefit of heat rate improvement is calculated separately.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".