MétaCan
Menu
Back to cohort
Record W2966450505 · doi:10.22215/etd/2015-10772

Small-signal Stability Analysis and Power System Stabilizer Design for Grid-connected Photovoltaic Generation System

2015· dissertation· en· W2966450505 on OpenAlexaff
Akshay Kashyap

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsCarleton University
Fundersnot available
KeywordsPhotovoltaic systemElectric power systemRenewable energyGrid-connected photovoltaic power systemTime domainGridSIGNAL (programming language)EngineeringStability (learning theory)Control theory (sociology)Power (physics)Stabilizer (aeronautics)Maximum power point trackingComputer scienceElectrical engineeringPhysicsVoltageMathematicsInverterMechanical engineering

Abstract

fetched live from OpenAlex

Solar energy is one of the emerging forms of renewable energy, and has been proved to be a potential source for generation of electricity. However, the rise in number of photovoltaic (PV) generators presents issues for electric power utilities. The objective of this thesis is to achieve stability for a grid-connected PV system with the proposed new power system stabilizer (PSS). Stability is attained by conducting small signal analysis and time domain analysis on the investigated PV system. First, time domain analysis on detailed and average PV system models without PSS is performed. Second, small signal stability analysis on average PV system model with and without PSS is performed. It is observed that the damping effect and the dynamic stability of the investigated PV system are achieved, with the help of the proposed new PSS.

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: Other · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.015

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.041
GPT teacher head0.237
Teacher spread0.195 · 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
GenreOther

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

Citations2
Published2015
Admission routes1
Has abstractyes

Explore more

Same topicPower System Optimization and StabilityFrench-language works237,207