Statistical Analysis Based Survey of Indian Renewable Energy Scenario
Bibliographic record
Abstract
Renewable energy is a solution for electricity generation for cleaner and green energy. The aim of this paper is to find the energy potential of India in terms of sources, per-capita energy consumption and the main potential consumers. Comparing consumption of fossil fuels and Renewable energy sources (RES) of India in 2019 and 2020 and finally to find whether there is any change in energy generation of two solar power plants in different geographical location of India with the help of independent t-test statistics. In this paper two statistical analysis are proposed. One is the statistical analysis of installed capacity, generation and consumption of fossil fuels and renewable energy in India. Other one is the statistical analysis of two solar power plants located at different geographical locations in India. From the statistical analysis it is found that, installed capacity of coal, RES and hydro is increased in 2020 as compared to 2019. Total demand in January 2020 is 2,77,140.33 MW whereas total installed capacity is 3,71,126 MW, this means that installed capacity is more but are not in running condition. From the statistical analysis of two independent solar power plants it is found that solar power plant-1 generates more energy but with high conversion loss hence poor efficiency.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".