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Record W2900854761 · doi:10.1109/tpel.2018.2883091

Investigation and Enhancement of Stability in Grid-Connected Active DC Distribution Systems With High Penetration Level of Dynamic Loads

2018· article· en· W2900854761 on OpenAlexaff
Ahmed M. I. Mohamad, Yasser Abdel‐Rady I. Mohamed

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2018
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsControl theory (sociology)GridPhasorEngineeringDC motorComputer scienceElectric power systemElectrical engineeringPower (physics)

Abstract

fetched live from OpenAlex

Nowadays, grid-connected active dc distribution systems are gaining widespread acceptance due to the remarkable development of the dc technology, high penetration levels of dc loads, and the market availability of dc-based distributed generators. One of the main features of dc systems is the elimination of multiple conversion stages required for variable frequency ac loads, such as variable-speed drive applications; therefore, dc distribution systems are considered as an efficient and cost-effective choice for supplying such dynamic loads. Induction motors (IMs) equipped with open-loop constant voltage/frequency (V/f) variable speed drives are considered as the workforce for many industrial loads due to their simplicity and satisfactory dynamic performance. However, V/f IM drives exhibit poor stability dynamics, particularly, at low-speed operation, which might negatively interact with the dc distribution system, leading to further stability degradation. Therefore, this paper investigates the interaction dynamics and the performance of a grid-connected dc distribution system with a high penetration level of dynamic loads. A detailed small-signal model of the entire system is developed to characterize the overall system stability margins with the help of the eigenvalues and impedance based analysis. Moreover, the uncertainties affecting the marginal stability such as motor operating speed, dc feeder length, and bus capacitance, are thoroughly addressed. It has been found that the dynamic loads in grid-connected dc distribution systems would exhibit instability issues due to various dynamic interactions; therefore, two different stabilizing compensation methods are proposed to mitigate the associating instability issues and enhance the system damping capability. Detailed time-domain non-linear simulations and experimental results are presented to validate the analytical results.

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 score0.002
Threshold uncertainty score0.004

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.198
Teacher spread0.188 · 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

Citations33
Published2018
Admission routes1
Has abstractyes

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