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Record W7105750269 · doi:10.5281/zenodo.17605818

IEA Wind TCP Task 51 "Forecasting for the weather driven energy system" - 2nd Austrian Workshop

2025· article· W7105750269 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Language
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsWind Energy Institute of Canada
FundersÖsterreichische Forschungsförderungsgesellschaft
KeywordsControl (management)Task (project management)Renewable energyGridWarning systemElectricityEvent (particle physics)

Abstract

fetched live from OpenAlex

The 2nd IEA Task 51 Austria Workshop “Weather-Driven Extreme Events in the Energy System” was held on 11 November 2025 at the Austro Tower in Vienna and brought together 125 experts from the energy sector, grid operation, meteorology, research, and public authorities. The workshop focused on the growing risks posed by weather-driven extreme events and their impacts on renewable energy generation, electricity markets, grid stability, and operational decision-making. The event was organized by GeoSphere Austria in cooperation with Austro Control Digital Services, with support from the Austrian Federal Ministry for Innovation, Mobility and Infrastructure (BMIMI) and the Austrian Research Promotion Agency (FFG). The programme covered a broad spectrum of topics, including: Extreme weather processes in the Alpine region and impacts on energy infrastructure Forecast errors and the limits of predictability Early warning systems and operational decision support Challenges in energy trading and grid management Digital twins, nowcasting systems, AI-driven forecasting, and meteorological risk indicators Weather-induced impacts on critical infrastructure (transmission and distribution grids, Austrian Railways, airport operations) This Zenodo record contains: Workshop programme (PDF) All presentations (PDF) as individual files Outputs from the interactive sessions (A–D) Optional: A ZIP archive containing all presentations in a single package All materials are part of the national Austrian activities within IEA Wind TCP Task 51: Forecasting for the Weather-Driven Energy System. Contributors (Presenters) Sabine Mitter (BMIMI) Bernhard Niedermoser (GeoSphere Austria) Florian Mader (WEB Windenergie) Gernot Waldsam (Austro Control Digital Services) Lukas Strauss (Austro Control Digital Services) Irene Schicker (GeoSphere Austria) Philipp Piber (Austro Control) Horst Brandlmaier (OeMAG) Short Talks – Energy Sector Andreas Nehls (Burgenland Energie Trading) Andreas Forster (oekostrom AG) Anna-Maria Tilg (Austrian Power Grid) Bernhard Spitzer (Energienetze Steiermark) Robert Grassinger (ÖBB Infrastruktur) Philipp Geier (Energie Steiermark Green Power) Short Talks – Research & Weather Laura Essl (Disaster Competence Network Austria – DCNA) Irene Schicker (GeoSphere Austria) Clemens Weiß (ACDS) Anton Fuxjäger (Enlite AI) Michael Kernitzkyi (JOANNEUM RESEARCH) Interactive Sessions Session A + D: Lukas Strauss Session B + C: Irene Schicker

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.000
Scholarly communication0.0020.000
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.230
Teacher spread0.193 · 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
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
Published2025
Admission routes1
Has abstractyes

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