MétaCan
Menu
Back to cohort
Record W2279959162 · doi:10.2172/814555

Spinning Reserves from Controllable Packaged Through the Wall Air Conditioner (PTAC) Units

2003· report· en· W2279959162 on OpenAlexfundno aff
Brendan Kirby

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicSmart Grid Energy Management
Canadian institutionsnot available
FundersPetroleum Technology Alliance CanadaOak Ridge National LaboratoryNew York State Energy Research and Development AuthorityOffice of Energy Efficiency and Renewable EnergyU.S. Department of EnergyDepartment of Water ResourcesCalifornia Energy Commission
KeywordsHVACSpinningEnvironmental scienceAir conditioningThermostatAutomotive engineeringController (irrigation)Computer scienceEngineeringElectrical engineeringMechanical engineering

Abstract

fetched live from OpenAlex

This report summarizes the feasibility of providing spinning reserves from packaged through the wall air conditioning (PTAC) units. Spinning reserves, together with non-spinning reserves, compose the contingency reserves; the essential resources that the power system operator uses to restore the generation and load balance and maintain bulk power system reliability in the event of a major generation or transmission outage. Spinning reserves are the fastest responding and most expensive reserves. Many responsive load technologies could (and we hope will) be used to provide spinning reserve. It is also easier for many loads (including air conditioning loads) to provide the relatively shorter and less frequent interruptions required to respond to contingencies than it is for them to reduce consumption for an entire peak period. Oak Ridge National Laboratory (ORNL) is conducting research on obtaining spinning reserve from large pumping loads and from residential and small commercial thermostat controlled heating, ventilation and air conditioning (HVAC) units. The technology selected for this project, Digi-Log's retrofit PTAC controller, offers significant advantages. To evaluate the availability of spinning reserve capacity from responsive heating and air conditioning loads, ORNL obtained data from a number of units operating over a year at a motel in the TVA service territory. A total of 24 PTAC units in as many rooms were fitted with Digi-Log's supervisory control unit that could be controlled from the motel front desk. Twelve of the rooms formed the group in which the controller was controlled from the hotel front desk only. The remaining twelve rooms were controlled by the occupant and formed the uncontrolled group. This enables us to evaluate the spinning reserve capacity from PTACS that were operating normally and from those under active energy management. A second generation of the Digi-Log controller that will respond quickly enough to provide spinning reserve has been designed but not yet manufactured. Manufacture of these units is pending arrival of funds from NYSERDA. The new Digi-Log equipment will utilize satellite signals from Skytel to activate the controller from a remote site by the ISO and to respond to curtailment events. PTACs account for approximately 3% of the total commercial cooling load in the US, equivalent to an average energy consumption rate of 3,000 MW with peak consumption being significantly higher. Hence PTACs alone represent a sizable opportunity for providing spinning reserves from load. The residential buildings sector cooling and heating load averages about 33,000 MW, more than 10 times the commercial PTAC load. The buildings sector represents an even greater opportunity than the PTAC commercial sector for providing spinning reserves from load. Technology to implement load curtailment and monitor its effect already exists and can readily be further customized to meet ISO and utility needs. Further research is needed to prove the technical feasibility of PTAC units and other small loads providing spinning reserves. Aggregation, communication, control, and monitoring issues remain to be addressed. If the technical issues can be resolved however, it is likely that system operators, loads, and regulators will have significant incentives to resolve these other resources since spinning reserve from load has the potential to provide large benefits to each community.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.489
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.247
Teacher spread0.202 · 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.

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

Citations6
Published2003
Admission routes1
Has abstractyes

Explore more

Same topicSmart Grid Energy ManagementFrench-language works237,207