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Record W7030322408

Modelling of voltage regulation issues in SWER systems using PSCAD/EMTDC

2006· article· en· W7030322408 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2006
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsnot available
Fundersnot available
KeywordsSoftwareEmtpVoltageVoltage regulationTransient (computer programming)Key (lock)Energy (signal processing)Distribution (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

An economic (low-cost) distribution system, called Single Wire Earth Return (SWER), has been used extensively in remote parts of Queensland and other states of Australia to deliver electrical energy to small customer loads, scattered sparsely over vast areas. Ergon Energy Corporation, a distribution utility in Queensland, has identified voltage regulation as one of the key issues being faced in this area, as loads continue to grow in rural distribution networks. In order to study voltage regulation issues of these systems, suitable models must be developed.Commercial software packages which are currently used by Ergon Energy, such as DINIS and PSS Adept do not offer all features required for modeling the SWER distribution systems in complete detail. Therefore, custom modeling using more flexible software tools available is deemed necessary. One such a software tool is PSCAD/EMTDC (PSCAD) developed by the Manitoba HVDC Research Centre in Canada. This is a commercial software package based on similar algorithms to most common electromagnetic transient programs such as EMTP or ATP.In this paper, modelling of SWER systems using PSCAD is discussed. Building blocks for the models of the distribution system components are developed. The effectiveness of this modelling approach is demonstrated using case studies of a real SWER distribution system. By using these models, the voltage regulation problem and the suitability of the proposed voltage control methods can be studied for a large network.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.815
Threshold uncertainty score0.997

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.044
GPT teacher head0.233
Teacher spread0.189 · 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.

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
Published2006
Admission routes1
Has abstractyes

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