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Enregistrement W2276328410

Study of stand-alone and grid-connected setups of renewable energy systems for Newfoundland

2015· dissertation· en· W2276328410 sur OpenAlexfundaboutno aff
Seyedali Meghdadi

Notice bibliographique

RevueMemorial University Research Repository (Memorial University) · 2015
Typedissertation
Langueen
DomaineEnergy
ThématiqueHybrid Renewable Energy Systems
Établissements canadiensnon disponible
Organismes subventionnairesNatural Sciences and Engineering Research Council of Canada
Mots-clésRenewable energyIntermittent energy sourceWind powerEnergy developmentRenewable resourceEnvironmental economicsGridGreenhouse gasEnvironmental scienceEngineeringEnvironmental resource managementDistributed generationGeographyElectrical engineeringEcologyEconomics
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Decreases in the cost of renewable energy systems such as solar panels and wind turbines, increasing demand for renewable energy sources to provide a sustainable future, and worldwide regulations to reduce greenhouse gas emissions have made renewable energy sources (RES) the strongest candidate to substitute for oil/gas power plants. Rich natural resources in Newfoundland and Labrador have established the province as a resource-based powerhouse. Hence, study of renewable energy setups for this region is of prominent importance. Renewable energy systems are chiefly categorized into the small-scale stand-alone and large-scale grid-connected systems. Generally, the term “large-scale renewable energy” refers to any large renewable energy projects (e.g. 100 KW or greater) which can make a significant contribution to energy needs. However, in this thesis it refers to wind farms due to the small amount of annual solar radiation in the Newfoundland region. The term “small-scale or local scale renewable energy” refers to personal and communal renewable energy harnessing systems mainly located in rural areas far from the grid. The largest differences between local scale and large scale systems are installation and maintenance costs, the magnitude of the energy harnessing systems, resilience ability (the capacity of a system to absorb disturbance and still retain its basic function), and energy storage capabilities. These differences mean that system design and analysis will be different for each category. This thesis aims to model, simulate and analyze the stand-alone and grid-connected setups of renewable energy systems customized for Newfoundland in order to meet current and future electricity needs with environmentally friendly, stable, and competitively priced power. It details potential design improvements as follows: (1) Small-scale renewable energy systems can be combined with conventional generators and energy storage devices in Hybrid Power Systems (HPS) to overcome the intermittency and uncontrollability issues of renewable power generators. Proper design of such a system is crucial for reliable, economic, and eco-friendly operation. In this thesis, a unique methodology for optimally sizing the combination of wind turbine, solar panel, and a battery bank in a Wind-PV Hybrid system is introduced. This method allows 2% lack of power supply in a year. Two off-grid systems are detailed and modeled in Matlab code and the sizing results of both systems are then compared to the results of the Homer software. Proposed method of sizing results in 30% of reduction to the initial cost of the system. (2) Solar panels are often installed in climates with a considerable amount of snowfall and freezing rain in winter. For instance, St. John’s on the Avalon Peninsula received more than three meters of snow in 2014. The optimal sizing objective of the solar panel in all renewable energy systems is to harness the maximum energy from solar insolation. Since snow accumulation poses an obstacle to the performance of solar panels, reducing their efficiency, it is essential to remove snow from panels as soon as possible. The design of a system that can accurately detect snow on panels and sends alerts in case of snow cover can play a significant role in the improvement of solar panel efficiency. This system was designed, built, and then tested for three months during the winter of 2014 in the engineering building at Memorial University of Newfoundland (47°34'28.9"N 52°44'07.8"W) using solar panels, a battery, a load, a microcontroller, a voltage and a current sensor, and a light dependent resistor. This system proves capable of precisely identifying more than 5 cm of snow accumulation on solar panels and sending alerts. (3) In large-scale renewable energy systems, proper investigation of the grid connection impact of wind farms is essential for the following reasons: Firstly, in wind turbines, generating systems are different from conventional grid coupled synchronous generators and interact differently with the power system. Secondly, the specific type of applied wind turbine has some aspects of interaction with the grid, particularly for wind turbines with and without power electronic converters. Analyzing connection of large-scale wind farms, simulating 500MW of wind capacity to the isolated grid of Newfoundland with the purpose of probing stability and reliability of the grid is conducted in “phasor simulation type” using Matlab/ Simulink. As a case study, the impact of the Fermeuse wind farm (46ᵒ58′42′′N 52ᵒ57′18′′W) on the isolated grid of Newfoundland is explored in “discrete simulation type” for three permissible scenarios, which are constant wind speed, variable wind speed, and reconnection of the wind farm to the grid. Results indicate that variable wind speeds cause very small fluctuations in the frequency and the current injected into the grid, meaning the grid is quite stiff. Also, system trip and reconnection will result in a frequency variation of 0.35 Hz, where some harmonics coming from the converter can be noticed, and voltage variation of less than 5%.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,668
Score d'incertitude au seuil0,660

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,034
Tête enseignante GPT0,270
Écart entre enseignants0,236 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission2
Résumé présentoui

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