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Record W7036880796

Comparison of Different Photovoltaic Park Models for Electromagnetic Transient Studies

2023· other· fr· W7036880796 on OpenAlexfundno aff

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2023
Typeother
Languagefr
FieldAgricultural and Biological Sciences
TopicMediterranean and Iberian flora and fauna
Canadian institutionsnot available
FundersPolytechnique Montréal
KeywordsRenewable energyTransient analysisPhotovoltaic systemElectric powerElectric power systemElectricity generation
DOInot available

Abstract

fetched live from OpenAlex

RÉSUMÉ: Les énergies renouvelables ont récemment retenu plus d'attention et ont été considérablement développées et installées en raison du réchauffement climatique et de l'inquiétude internationale pour les combustibles fossiles traditionnels. Étant donné que la stabilité des réseaux électriques peut être affectée par une forte pénétration des centrales photovoltaïques connectées au réseau, le développement de modèles précis et efficaces joue un rôle important dans la caractérisation du comportement du système électrique. De plus, afin d'étudier l'interaction des parcs photovoltaïques avec le réseau, des simulations EMT sont nécessaires. L'objectif de ce projet de recherche est d'examiner de manière exhaustive les différents modèles de parcs PV pour la simulation des EMT. Les systèmes solaires photovoltaïques sont basés sur des onduleurs. Par conséquent, une comparaison des différents modèles d'onduleurs utilisés dans les parcs photovoltaïques tels que le modèle détaillé, le modèle de valeur moyenne et le modèle de fonction de commutation est présentée. De plus, ces modèles sont comparés en termes de précision et de charge de calcul. En outre, cette thèse présente des comparaisons complètes des modèles de parcs photovoltaïques et de leurs performances à l'aide d'un système de référence. Enfin, les différences entre les différents modèles de parcs photovoltaïques et le modèle approprié pour chaque objectif de simulation sont discutés. ABSTRACT: Renewable energy has recently absorbed more attention and has been considerably expanded and installed due to global warming and international concern for traditional fossil fuel. Since stability of power grids can be affected by high penetration of grid-connected PV power plant, developing accurate and efficient models has important role in characterization of power system behavior. Moreover, in order to study the interaction of PV parks with the network, accurate EMT simulations are required. The objective of this research project is to comprehensively review the different PV park models for the EMTs simulation. The solar PV systems are based on inverters. Therefore, a comparison on the different inverter models used in PV parks such as detailed model, average value model and switching function model is presented. Moreover, these models are compared in terms of accuracy and computational burden. Furthermore, this thesis presents comprehensive comparisons of PV park models and their performance using a benchmark system. Finally, the differences of different PV park models and the suitable model for each simulation purpose are discussed.

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: none
Teacher disagreement score0.007
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.043
GPT teacher head0.272
Teacher spread0.229 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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