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Record W7133070280

Modeling, Optimization and Large-scale Grid Integrations of Solar Photovoltaic Energy in Ontario's Electricity System

2016· dissertation· W7133070280 on OpenAlexaffabout
David B. Richardson

Bibliographic record

VenueTSpace · 2016
Typedissertation
Language
FieldEnvironmental Science
TopicPhotovoltaic Systems and Sustainability
Canadian institutionsUniversity of Toronto
FundersNational Renewable Energy Laboratory
KeywordsPhotovoltaic systemRenewable energyElectricityGrid paritySolar energyElectricity generationEnergy supplyFossil fuelStand-alone power systemEnergy development
DOInot available

Abstract

fetched live from OpenAlex

Modern societies' increasing demand for and reliance on energy, primarily supplied by fossil fuels, and the resulting carbon dioxide emissions that lead to climate change is a complex issue with significant implications for the future well-being of society and the environment. Decoupling economic activity and energy production from carbon is essential to effectively deal with both issues simultaneously. Solar photovoltaic (PV) electricity has the potential to help meet future energy demands while significantly reducing the climate impact of energy production; however, large-scale integration of solar PV into existing electricity systems presents technical challenges that must be addressed if solar is to contribute to a sustainable energy future. This thesis presents four research modules that form a comprehensive evaluation of the technical and economic feasibility of integrating renewable energy, specifically solar PV energy, into the Ontario electricity system. The findings indicate that solar PV can supply a significant portion (8-30%) of total electricity supply if substantial changes are made to the existing grid. Specifically, energy storage and more flexible supply are required to deal with increased ramping rate requirements. As the effects of global warming and peak oil become apparent, and as new technologies for smart grids and distributed generation are introduced into the grid, it will be useful to have a comprehensive understanding of how to plan for the integration of renewables from an electricity generation perspective. The research in this thesis is a thorough analysis of one aspect of solar PV deployment that will be useful to encourage grid integration. This research can be combined with similar assessments by others of storage, demand management, wind and biomass energy sources to give a comprehensive understanding of how to plan energy generation investments to sustainably meet future needs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.477

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.262
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2016
Admission routes2
Has abstractyes

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