MétaCan
Menu
Back to cohort
Record W2725176907

Seawater PHES to Facilitate Wind Power Integration in Dry Coastal Areas – Duqm Case Study

2017· article· en· W2725176907 on OpenAlexaff
Mohammed Albadi, Adil S. Al-Busaidi, Ehab F. El‐Saadany

Bibliographic record

VenueInternational Journal of Renewable Energy Research · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicWater-Energy-Food Nexus Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsRenewable energyWind powerPumped-storage hydroelectricityIntermittent energy sourceEnvironmental scienceEnergy storageMarine energyElectric power systemPower stationFossil fuelEngineeringMarine engineeringEnvironmental economicsDistributed generationPower (physics)Waste managementElectrical engineering
DOInot available

Abstract

fetched live from OpenAlex

Currently, the contribution of renewable energy resources, such as wind power, in power systems is increasing in large, interconnected systems. However, the intermittent nature of renewable energy poses a profound challenge to power system operation and planning. Using energy storage systems can facilitate wind power integration in isolated systems. Pumped hydro energy storage (PHES) plants are by far the most established technology for energy storage on a large-scale. In dry coastal areas, seawater PHES can be used to facilitate the integration of large scale renewable energy resources. In Oman, the potential of renewable energy resources has not been exploited yet. This article presents a techno-economic evaluation case study of using a combined wind power and PHES power plant to highlight its economic feasibility. PHES systems can enable higher penetration of renewable energy in isolated systems, therefore reducing the dependency on fossil fuels.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.092
GPT teacher head0.355
Teacher spread0.263 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations7
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Renewable Energy ResearchSame topicWater-Energy-Food Nexus StudiesFrench-language works237,207