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Optimal Coordinated Control of Multi-Renewable-to-Hydrogen Production System for Hydrogen Fueling Stations

2021· article· en· 163 citations· W3175253211 on OpenAlex· 10.1109/tia.2021.3093841

Why is this work in the frame?

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

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
Meta-epidemiology (narrow)
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Bench or experimentalConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: none
Teacher disagreement score
0.906
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.017
GPT teacher head0.254
Teacher spread
0.236 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

Under the pressure of climate change, the demands for alternative green hydrogen (H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) production methods have been on the rise to conform to the global trend of transition to a H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> society. This article proposes a multirenewable-to-hydrogen production method to enhance the green H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> production efficiency for renewable-dominated hydrogen fueling stations (HFSs). In this method, the aqueous electrolysis of native biomass can be powered by wind and solar generations based on electrochemical effects, and both electrolysis current and temperature are taken into account for facilitating on-site H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> production and reducing the electricity consumption. Moreover, a capsule network based H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> demand forecasting model is formulated to estimate the gas load for HFS by extracting the underlying spatial features and temporal dependencies of traffic flows in the transportation network. Furthermore, a hierarchical coordinated control strategy is developed to suppress high fluctuations in electrolysis current caused by volatility of wind and solar outputs based on model predictive control framework. Comparative studies validate the superior performance of the proposed methodology over the power-to-gas scheme on electrolysis efficiency and economic benefits.

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.

The record

Venue
IEEE Transactions on Industry Applications
Topic
Electrocatalysts for Energy Conversion
Field
Energy
Canadian institutions
University of Saskatchewan
Funders
Innovation and Technology CommissionNational Natural Science Foundation of China
Keywords
Hydrogen productionHydrogenComputer scienceRenewable energyEnvironmental scienceChemistryEngineeringElectrical engineeringOrganic chemistry
Has abstract in OpenAlex
yes