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Record W4407948556 · doi:10.1109/mpe.2024.3427727

Macrogrids and Supergrids: Wide Area Transmission to Improve Electrification and Variable Renewable Energy Use

2025· article· en· W4407948556 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

VenueIEEE Power and Energy Magazine · 2025
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsElectrovaya (Canada)
Fundersnot available
KeywordsRenewable energyElectrificationVariable (mathematics)Variable renewable energyComputer scienceEnvironmental economicsEnvironmental scienceElectrical engineeringEngineeringEconomicsElectricityEnergy storagePhysicsMathematicsPower (physics)

Abstract

fetched live from OpenAlex

Studies have shown that wide area high-voltage dc (HVdc) electric power grids will be needed for the future. In North America, these are known as “macrogrids” and in Europe, “supergrids,” which are sometimes referred to as “hypergrids.” There are obstacles in the way to achieving these wide area grids, however. What are these obstacles, and how can they be overcome? Such obstacles include passing through multiple jurisdictions and obtaining permitting. The NIMBY challenge is one such issue. Of course, a wide area transmission grid will pass through different countries and states, adding to the permitting challenge. The processes that are being applied include the use of rights-of-way of existing railroads or highways. Underwater locations may include those beneath lakes and rivers as well as those undersea. In the United States, the right-of-way of a rail line is being used to traverse several states for 2,100-MW, ±525-kV HVdc cables. Roadside rights-of-way are also under active consideration for HVdc cables for the macrogrid.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.951
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.003
GPT teacher head0.172
Teacher spread0.169 · 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