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Record W2551253881 · doi:10.1109/pesgm.2016.7741813

Coordinated control of PV solar system as STATCOM (PV-STATCOM) and Power System Stabilizers for power oscillation damping

2016· article· en· W2551253881 on OpenAlexaff
Hesamaldin Maleki, Rajiv K. Varma

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsWestern University
Fundersnot available
KeywordsElectric power systemPhotovoltaic systemGrid-connected photovoltaic power systemControl theory (sociology)AC powerController (irrigation)EngineeringInverterPower (physics)Maximum power point trackingComputer scienceElectrical engineeringVoltageControl (management)Physics

Abstract

fetched live from OpenAlex

This paper presents a novel control of PV solar farm as a STATCOM (PV-STATCOM) coordinated with Power System Stabilizers (PSSs) for damping of electromechanical oscillations in a power system. A two-area power system with a 150 MW PV solar plant connected at the midpoint of the tie line is simulated in PSCAD/EMTDC software. During contingencies, the capacity of the PV inverter remaining after real power generation is utilized for dynamic reactive power exchange to accomplish power oscillation damping. The advantage of master-slave feature in PSCAD/EMTDC software is utilized for performing the optimization and controller coordination. It is demonstrated that a coordinated control of PV-STATCOM and PSS can effectively enhance the damping of power oscillations, leading to higher power transfers in lines. This novel control of PV solar farms will result in a more optimal utilization of the expensive PV system asset for grid stabilization and enhancement of power transmission capability.

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)0.000
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.202
Teacher spread0.196 · 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

Citations19
Published2016
Admission routes1
Has abstractyes

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