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Record W4400676524 · doi:10.1049/icp.2024.1856

Initial perspective of hybrid energy storage in zero carbon energy systems of a remote community of northern Canada

2024· article· en· W4400676524 on OpenAlexaffabout
Hayley Knowles, Andrew Swingler, Lukas G. Swan

Bibliographic record

VenueIET conference proceedings. · 2024
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsUniversity of Prince Edward IslandDalhousie University
Fundersnot available
KeywordsPerspective (graphical)Zero (linguistics)Energy (signal processing)Energy storageCarbon fibersEnvironmental scienceZero-point energyComputer scienceEngineering physicsEnvironmental economicsMaterials scienceEngineeringPhysicsThermodynamicsEconomicsArtificial intelligenceAlgorithm

Abstract

fetched live from OpenAlex

We review towards zero and zero carbon remote community energy systems using wind and solar electricity generation combined with battery and thermal energy storage systems. Systems are modelled in the context of the Xeni Gwet’in First Nation Community located in the Nemiah Valley in British Columbia, Canada. The community has a population of 200 residents, most of whom are connected to the local microgrid. The goal of this research was to (1) investigate how low-cost thermal energy storage impacts the levelized cost of energy of these systems, and (2) assess the sensitivity of unmet energy capacity of the system at varying storage costs. Electrical and thermal load profiles for the community were developed and determined to average a combined annual load of 2 GWh with a peak of 900 kW. A model of the proposed system was built in HOMER Pro® and sensitivity analysis of PV, wind, and hybridized energy storage costs was conducted. Results indicate that as wind and PV costs are projected to decrease, minimizing the levelized cost of energy of the energy system is less dependent on thermal energy storage cost.; this correlation decreases as unmet capacity increases. Moreover, the analysis suggests that these systems yield greater than 70% curtailment of solar and wind energy, regardless of energy storage costs.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.236
Teacher spread0.217 · 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 designTheoretical or conceptual
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
Published2024
Admission routes2
Has abstractyes

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