MétaCan
Menu
Back to cohort
Record W2014278132 · doi:10.1109/pesmg.2013.6672959

Overview of FERC Order No. 755 and proposed MISO implementation

2013· article· en· W2014278132 on OpenAlexaff
Rae-Anne Miller, Bala Venkatesh, Daniel Cheng

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsElectricityOrder (exchange)Service providerService (business)Frequency regulationElectric power systemGovernorAutomatic frequency controlAutomatic Generation ControlComputer scienceElectricity marketTelecommunicationsElectrical engineeringBusinessFinancePower (physics)EngineeringMarketing

Abstract

fetched live from OpenAlex

Frequency regulation is an important feature of electric power systems. In several electricity markets, it is traded as an ancillary service and is procured by the independent system operator (ISO). Typically service providers are conventional generators with automatic governor control. In the recent past, energy storage devices such as flywheels have started offering frequency regulation service. With these devices capable of providing a better regulation in comparison with conventional generators, there has been a move to alter FERC regulations to remunerate ancillary service providers of frequency regulation based on their quality and quantity of service. This paper reviews various forms of energy storage systems that hold a promise for a role in electricity markets. Thereafter, the paper reports and discusses the new Order 755 promulgated by FERC to remunerate frequency regulation service providers. Finally the paper reports the proposed MISO implementation of FERC Order 755 and a few examples to illustrate it.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.042
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0030.002
Scholarly communication0.0080.004
Open science0.0040.002
Research integrity0.0080.004
Insufficient payload (model declined to judge)0.0210.010

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 head0.030
GPT teacher head0.325
Teacher spread0.296 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations7
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced battery technologies researchFrench-language works237,207