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Record W2601452290

Optimal Siting and Sizing of Solar Photovoltaic Distributed Generation to Minimize Loss, Present Value of Future Asset Upgrades and Peak Demand Costs on a Real Distribution Feeder

2011· dissertation· en· W2601452290 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUWSpace (University of Waterloo) · 2011
Typedissertation
Languageen
FieldEngineering
TopicOptimal Power Flow Distribution
Canadian institutionsnot available
Fundersnot available
KeywordsSizingPhotovoltaic systemAsset (computer security)Distributed generationValue (mathematics)Environmental economicsReliability engineeringBusinessComputer scienceEnvironmental scienceEngineeringElectrical engineeringEconomicsRenewable energyChemistry
DOInot available

Abstract

fetched live from OpenAlex

The increasing penetration of distributed generation (DG) in power distribution systems presents technical and economic benefits as well as integration challenges to utility engineers. Governments are beginning to acknowledge DG as an economically viable alternative to deferring investment at generation, transmission and distribution levels, meeting demand growth and improving distribution network performance and security. DG technology is rapidly maturing in Ontario due to government economic incentives promoting connection, specifically, the Ontario’s Feed-In-Tariff (FIT) Program. 
\n Optimal sizing and siting of DG is well researched, traditionally studying the technical impact on distribution system such as real power loss reduction and voltage profile improvement. Equally common objectives studied are the economics of DG installation which are useful for the developer when deciding when and where to install. Although DG represents a “non-wires” solution to network asset reinforcement, the direct economic benefit to the host utility from promoting DG uptake is not fully understood by utility planners and asset managers. Some DG based asset reinforcement deferral work has been performed in the UK and Italy but is mainly at the transmission level and is not part of an overall strategy that could be applied by a utility. 
\nThis research presents a comprehensive three stage technique: optimal siting, optimal sizing and financial evaluation of cost savings over a defined planning period to quantify the economic benefit to a Local Distribution Company (LDC) of solar photovoltaic (PV) DG connections on an actual distribution feeder. Optimal sites for PV DG are determined by applying the power loss sensitivity factor method to the test feeder. The objective functions used to determine cost savings consist of loss minimization, asset investment deferral, and peak demand reduction to identify an optimal DG penetration limit. Furthermore, a utility planner can identify an optimal DG penetration limit, encourage uptake at preferred locations that would benefit the LDC, and use the positive impact of DG at existing locations as part of an asset management strategy to prioritize and schedule future asset reinforcement upgrades.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.195
Teacher spread0.187 · 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