MétaCan
Menu
Back to cohort
Record W4235853182 · doi:10.26868/25222708.2019.210320

A Co-simulation Framework for Assessing the Interaction between Heat Pumps and the Low Voltage Grid on a District Scale

2020· article· en· W4235853182 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBuilding Simulation Conference proceedings · 2020
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Energy Management
Canadian institutionsNatural Resources Canada
FundersMinisterio de Economía y CompetitividadEuropean Commission
KeywordsGridScale (ratio)Computer scienceVoltageEnvironmental scienceMechanical engineeringElectrical engineeringEngineeringPhysicsGeology

Abstract

fetched live from OpenAlex

The traditional unidirectional-flow electricity grid is evolving and integrating active power electronics, controllable loads, and Distributed Energy Resources (DERs). The design and validation of innovative electric networks is challenging and since experimental data is not easily obtained on such large scales, simulation-based approaches are adopted to support their development. The simulation and validation of the grid at a system level requires high resolution models of multiple domains involving the end user, the electric grid, and the interaction between them, and a co-simulation approach is adopted in order to encompass all elements and take advantage of the many specialized tools that address each of them separately. This paper will present a co-simulation framework that uses the Functional Mock-up Interface (FMI) standard in order to combine TRNSYS for the building domain and the Python package PandaPower for the electric grid domain.

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.

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)0.001
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 score0.556
Threshold uncertainty score0.665

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.037
GPT teacher head0.310
Teacher spread0.273 · 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