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Record W2041595017 · doi:10.1177/0270467608315530

Environmental and Economic Impacts of Integrating Photovoltaic and Wind-Turbine Energy Systems in the Canadian Residential Sector

2008· article· en· W2041595017 on OpenAlexaffabout
Ali M. Syed, Alan S. Fung, V. Ismet Ugursal

Bibliographic record

VenueBulletin of Science Technology & Society · 2008
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsToronto Metropolitan UniversityDalhousie University
Fundersnot available
KeywordsGreenhouse gasRenewable energyPhotovoltaic systemElectricityKyoto ProtocolNet meteringElectricity generationWind powerFossil fuelEnvironmental scienceEnvironmental economicsNatural resource economicsEngineeringWaste managementEconomicsDistributed generation

Abstract

fetched live from OpenAlex

The Canadian residential sector contributes approximately 80 megatons of GHGs to the environment yearly. With the ratification of Kyoto Protocol, Canada has committed to reduce its 1990 GHG emission levels by at least 5% between 2008 and 2012. To meet this target, Canada must evaluate and exploit all feasible means to reduce fossil fuel energy consumption and GHG emissions. Test-case Canadian houses were modeled in the building-energy simulation software ESP-r. Requisite housing stock data were extracted from Canada's residential end-use energy surveys. Photovoltaic and wind-turbine energy systems were assessed for their contribution to electricity generation and GHG savings. Typical household electrical consumption versus renewable electricity generation was assessed to estimate the GHG reduction, cost saving in electricity, and the impact of these technologies on single detached houses. With the use of net-metering, 100% of electricity requirements can be met by these technologies in certain cases, resulting in significant reductions in GHG emissions.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score0.967

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 studies0.0000.001
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 head0.004
GPT teacher head0.167
Teacher spread0.163 · 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 designSimulation or modeling
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

Citations9
Published2008
Admission routes2
Has abstractyes

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