Power Quality and Dynamic Enhancement of Remote Gas Field Generation based on Smart Power Converters
Notice bibliographique
Résumé
Natural gas is a cornerstone of global power generation, balancing reliability and environmental sustainability. In Alberta, Canada, which holds one of the largest natural gas reserves in the country, natural gas-fired power generation plays a crucial role in meeting both provincial and export energy demands. As many of these resources are situated in remote northern and western regions, building power plants near gas fields presents a practical solution to minimize transmission losses and lower fuel transportation costs, thereby enhancing efficiency and reducing environmental impact. Additionally, integrating on-site greenhouses allows residual heat and carbon emissions to be repurposed for crop cultivation, further enhancing the sustainability of power generation. However, due to their remote locations, these plants are typically connected to weak utility grids with high line impedance, which exacerbates power quality issues. Nonlinear loads, such as fluctuating demands from greenhouse grow lights and residential heating, ventilation, and air conditioning (HVAC) systems, lead to overvoltage and harmonic distortions. Moreover, the weak grid environment amplifies dynamic interactions among multiple generators, further challenging system stability. These issues threaten the stability and reliability of power systems, necessitating innovative solutions to enhance operational efficiency. To address these challenges, this thesis proposes a system architecture where the gas turbine generator is interfaced with the grid via a back-to-back (B2B) converter. Control strategies are developed for both grid-following and grid-forming modes, enabling coordinated regulation of active power, AC voltage, and\nDC-link voltage. Leveraging flexible inverter controls, the proposed approach enhances both power quality and the dynamics in multi-machine systems. Building on this foundation, the thesis also investigates control selection and parameter tuning through eigenvalue analysis to ensure stability under varying grid strengths. Small-signal analysis of the grid-side converter provides insight into stability conditions and aids in optimizing parameter design. For large disturbances such as grid-side faults, a crowbar protection strategy is introduced to absorb the power imbalance between converters, effectively suppressing DC-link overvoltage and improving fault ride-through capability. To validate the proposed methods, a practical gas-based power system is modeled and tested through real-time simulations using RT-LAB. The results confirm substantial improvements in power quality and dynamic performance. Additional analysis highlights the influence of grid strength and control parameters on overall system behavior, and verifies the effectiveness of the crowbar strategy in protecting the B2B converter during faults. Overall, the proposed methods significantly enhance the power quality and operational stability in remote gas-based power systems. The thesis also provides comprehensive guidance on system configuration, including control strategy selection, parameter tuning under different grid strengths, and fault response design. These findings contribute to the development of more resilient, efficient, and sustainable gas generation systems in remote situations.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».