Coal Switching Evaluation on Coal-Fired Power Plants: Case Study in Indonesia
Bibliographic record
Abstract
Indonesia’s energy mix is still dominated by coal, reaching 67.21% in 2022. On the other hand, the coal crisis is a significant challenge to providing electricity needs. Hence, the coal specifications consumed are commonly lower than the coal-fired power plant’s design. In addition, efficiency is essential to reduce production costs, and coal switching is an alternative resolution to keep electricity production. This study compares two coal with a calorific value of 4,500 kcal/kg and 4,200 kcal/kg by considering the equivalent availability factor (EAF), equivalent forced outage rate (EFOR), production cost, and environmental aspect in six months period. The result shows EAF are 89.65% and 89.36%, EFOR 2.98% and 4.02%, cost savings on fuel components is 9.07-32.80 Rp/kWh, and emission concentration is below the standard. It was found that the coal switching program did not have a negative impact on operational, financial, and environmental aspects.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".