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An Integrated Distributed Generation Optimization Model for Distribution System Planning

2005· article· en· 519 citations· W2096720283 on OpenAlex· 10.1109/tpwrs.2005.846114

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
Meta-epidemiology (narrow)
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Simulation or modelingConsensus signal: Simulation or modeling
Genre
Candidate signal: EmpiricalConsensus signal: none
Teacher disagreement score
0.984
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.019
GPT teacher head0.239
Teacher spread
0.221 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

This paper proposes a new integrated model for solving the distribution system planning (DSP) problem by implementing distributed generation (DG) as an attractive option in distribution utilities territories. The proposed model integrates a comprehensive optimization model and planner's experience to achieve optimal sizing and siting of distributed generation. This model aims to minimize DG's investment and operating costs, total payments toward compensating for system losses along the planning period, as well as different costs according to the available alternative scenarios. These scenarios vary from expanding of an existing substation and adding new feeders to purchasing power from an existing intertie to meet the load demand growth. Binary decision variables are employed in the proposed optimization model to provide accurate planning decisions. The present worth analysis of different scenarios is carried out to estimate the feasibility of introducing DG as a key element in solving the DSP problem.

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.

The record

Venue
IEEE Transactions on Power Systems
Topic
Optimal Power Flow Distribution
Field
Engineering
Canadian institutions
University of Waterloo
Funders
not available
Keywords
Distributed generationPlannerSizingKey (lock)EngineeringPurchasingMathematical optimizationOperations researchComputer scienceOperations managementRenewable energy
Has abstract in OpenAlex
yes