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A Review of Interoperability Challenges and Solutions Towards a Digital Twin of the European Electricity Grid

2024· review· en· W4405522661 on OpenAlexaff
S. Diakakis, Pencho Zlatev, Nikolay Palov, Theodoros I. Maris, A. Santas, M. Papadimitriou

Bibliographic record

Venuenot available
Typereview
Languageen
FieldEngineering
TopicDigital Transformation in Industry
Canadian institutionsOptech (Canada)
FundersEuropean Commission
KeywordsInteroperabilityGridComputer scienceElectricityWorld Wide WebElectrical engineeringEngineeringGeography

Abstract

fetched live from OpenAlex

A significant challenge for the European energy system decarbonization transition and climate neutrality is the cost-competitiveness of the renewable sources as well as the optimal system integration of these distributed renewable assets in a cost-effective way, particularly making sure that renewables will best adapt to grid connection regulations and operational constraints. In the smart grids’ operation, there are real-time data exchanges, interoperability and Open Application Programmable Interfaces as critical technology building blocks to enable plug and play data interfaces from DERs located into prosumer houses into energy markets federated through Flexibility Service providers, Market Operators as well as TSOs and DSOs. This information will enable the development of European digital twin of the electricity grids, which is the scope of the European project TwinEU. This work's goal is to present the results of a desktop analysis through the European projects to identify challenges and gaps in data interoperability and interfaces for the electricity grid operation. The analysis is carried out during the TwinEU project

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: Review · Consensus signal: Review
Teacher disagreement score0.854
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.084
GPT teacher head0.287
Teacher spread0.203 · 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
GenreReview

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

Citations4
Published2024
Admission routes1
Has abstractyes

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