Cost Benchmarking of Generation Utilities Using DEA: A Case Study of India
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Technical efficiency of electric utility is the critical element for its competitiveness in the electricity market and very relevant in the Indian electricity sector presently. This paper is aimed to measure the efficiencies of 30 state owned electric generation utilities/companies for the year 2007-08 by applying DEA models with single input and two outputs. The input used is total cost and outputs are units of energy generated and total energy sold or consumed. Cost benchmarking has been carried out so that cost controls can be implemented. In addition, the target evaluation for input cost has also been done. The result of this model shows that GENCOs are generally inefficient in cost frontier and there is an urgent need for intro inspection. This will help for GENCOs. The result shows that the total average of overall, technical and scale efficiencies are 46%, 75.1% and 60% respectively. This efficiency measurement assists the utilities by identifying their shortcomings, setting targets and trying to reach the set targets.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it