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CONCEPTS ON MARKET-ORIENTED TRANSMISSION INVESTMENT

2007· article· en· W1981693436 on OpenAlexvenueno aff
David Enke, Badrul Chowdhury, Gregory M. Gelles, Kamil Staněk

Bibliographic record

VenueInternational Journal of Power and Energy Systems · 2007
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsInvestment (military)BusinessTransmission (telecommunications)Industrial organizationTelecommunicationsComputer sciencePolitical science

Abstract

fetched live from OpenAlex

For several years, much of the deregulated power industry has appeared to be in repair mode; in other words, the general approach seem to be fix a problem if it shows up and continue to function until another problem is encountered. Although a free market should generate enough signals within the confines of the market rules to sustain itself in the long run, such is not the norm in the case of the electricity industry. In this paper, market incentives for transmission capacity expansion are explored. A real options framework is presented whereby transmission investment can be funded and financial risks can be minimized. A game theory strategy that can be combined with real options is then introduced for calculating the value and cost of transmission investment. As an example, the use of game theory for allocating cost is presented with a simple three-generator, two-bus example. The proposed method has the advantage of considering the social welfare of all participants in order to ensure that the costs are being fairly allocated to those market participants that will realize the most benefit.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.383

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 head0.004
GPT teacher head0.224
Teacher spread0.220 · 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 designNot applicable
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
Published2007
Admission routes1
Has abstractyes

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