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Record W1031890203 · doi:10.1139/tcsme-2009-0003

DECENTRALISED GENERATION IN VICTORIA, AUSTRALIA: IMPLICATIONS FOR ELECTRICITY SUPPLY RELIABILITY

2009· article· en· W1031890203 on OpenAlexvenueno aff
Naomi Rachel Brammer, Mir-Akbar Hessami

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsElectricityMains electricityRenewable energyElectricity generationReliability (semiconductor)Wind powerNameplate capacityEnvironmental economicsFossil fuelElectricity demandEnvironmental scienceReliability engineeringBusinessEngineeringEconomicsPower (physics)Electrical engineeringWaste management

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.219
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicIntegrated Energy Systems OptimizationFrench-language works237,207