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Record W7154207008 · doi:10.5281/zenodo.19566273

Flexibility In Future Power Systems

2019· article· en· W7154207008 on OpenAlexaboutno aff
Emil Hillberg, Antony Zegers, Barbara Herndler, Steven Wong, J. Pompee, Jean‐Yves Bourmaud, Sebastian Lehnhoff, Gianluigi Migliavacca, Kjetil Uhlen, Irina Oļeiņikova, Hjalmar Pihl, Markus Norström, Mattias Persson, Joni Rossi, Giovanni Beccuti

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2019
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Energy Management
Canadian institutionsnot available
Fundersnot available
KeywordsFlexibility (engineering)Electric power systemElectricityPower gridPower (physics)Grid

Abstract

fetched live from OpenAlex

Solutions providing advances in flexibility are of utmost importance for the future power system.However, flexibility is not a unified term and is lacking a commonly accepted definition. The flexibility term is used as an umbrella covering various needs and aspects in the power system which complicates the discussion on flexibility and craves for differentiation to enhance clarity. ISGAN Working Group 6 has dedicated an activity on flexibility with the intention to support an increased understanding of the flexibility concept, proposing categorisation of flexibility needs in the power system. This activity resulted in several publications with contributions from parties in: Sweden, Austria, Canada, France, Germany, Italy, Norway, and Switzerland. The final results and conclusions of this activity were presented at a dedicated ISGAN Webinar, November 2019. In the Fact Sheet: Grid Evolved – Power System Flexibility, the condensed knowledge from this activity, with collaboration with Mission Innovation, was published for the 10th Clean Energy Ministerial in Vancouver, Canada, May 2019. In the Discussion Paper (DOI: 10.13140/RG.2.2.22580.71047), the full report is provided from this activity, including description of the flexibility categories: Flexibility for Power, Flexibility for Energy, Flexibility for Transfer Capacity, and Flexibility for Voltage. The Leaflet: Power system flexibility – the ability to manage change presents an executive summary of the discussion paper, giving a good insight into the work. This leaflet was published for the ISGAN Conference The future of electricity markets in a low carbon economy in Stockholm, Sweden April 2019. The Scientific paper: Flexibility to support the future power systems, based on the discussion paper, was published for the CIGRE Symposium in Aalborg, Denmark, June 2019. This publication was prepared for the International Smart Grid Action Network (ISGAN) by Working Group 6. ISGAN is organized as the Implementing Agreement for a Co-operative Programme on Smart Grids (ISGAN) and operates under a framework created by the International Energy Agency (IEA). The views, findings and opinions expressed herein do not necessarily state or reflect those of any of ISGAN’s participants, any of their sponsoring governments or organizations, the IEA Secretariat, or any of its member countries.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0020.004
Scholarly communication0.0060.007
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0270.004

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 head0.014
GPT teacher head0.201
Teacher spread0.187 · 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 designSimulation or modeling
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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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