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Feasibility Study of Hybrid Wind-Diesel-Battery Power Generating Systems: Parametric and Sensitivity Analysis

2018· article· en· W2806536205 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMATEC Web of Conferences · 2018
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsCegep de Sept Iles
Fundersnot available
KeywordsRenewable energyWind powerHybrid powerEnvironmental scienceHybrid systemAutomotive engineeringDiesel fuelGridPhotovoltaic systemFossil fuelSoftwareGrid connectionMeteorologyComputer scienceEngineeringPower (physics)Electrical engineeringWaste managementGeography

Abstract

fetched live from OpenAlex

The renewables energies are being used to reduce the environmental pollution, combat the climate change and burning of fossil fuels. For remote or decentralized areas, where grid connection is very complex, renewable energy generation system can be a reliable and optimized source of energy. Moreover, wind-diesel-solar hybrid system technology promises lots of opportunities in remote areas which are far from the main grid and are supplied by diesel gensets. This paper is based on the analysis of a hybrid energy system for optimization. The analysis of the hybrid system is realized in the HOMER software package. The HOMER software was utilized as the assessment tool with modeling performed with hourly data of wind speed, solar radiation and load. In this study, the remote village of Tuktoyaktuk situated in Northwest Territories of Canada has been taken for the discussion of the optimization analysis of a hybrid energy generation system.

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)0.002
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 score0.411
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.029
GPT teacher head0.265
Teacher spread0.236 · 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