DECENTRALISED GENERATION IN VICTORIA, AUSTRALIA: IMPLICATIONS FOR ELECTRICITY SUPPLY RELIABILITY
Bibliographic record
Abstract
Distributed or decentralised generation (DG) using advanced fossil fuel and renewable energy technologies is an attractive alternative to traditional electricity generation. Over 75% of new generating capacity installed in the Australian state of Victoria between 2000 and 2010 will be DG from gas turbines and wind farms. However, it is uncertain if this new capacity will be sufficient to maintain historic levels of electricity supply reliability. The contribution of DG to Victoria’s electricity supply in 2010 has been assessed, through analysis of modelled supply and demand data and comparisons with data from 2000. While it was assumed that new gas turbines will provide peak load and emergency generation, the role of wind farms was evaluated by considering their equivalent firm capacity estimated using statistical and probabilistic methods. Results show that all DG from gas turbines will contribute to Victoria's electricity supply in 2010, but only 4-30% of installed wind farm capacity can be considered firm or reliable. Technical performance indicators suggest that the new generating capacity will be unable to satisfy increased demand with adequate reliability. Additional base load capacity and demand reduction measures are required to ensure Victoria’s electricity supply reliability is maintained in the future.
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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 | 0.000 | 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 | 0.000 | 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".