Power Management and Control to Balance Residential Microgrids with Individual Phase-wise Generation and Storage
Notice bibliographique
Résumé
The past decade has seen a significant rise in proliferation of roof-top photovoltaic (PV) systems with storage units at residential sites. This has affected the way power system engineers and researchers have previously studied distribution systems as passive networks. With the introduction of these local distributed energy resources, a distribution system has become part of an active network. This modernization of the power distribution network, brings along with itself a number of key issues that need to be pro-actively tackled by the local utilities.\nIn North America, with family-owned roof-top PV systems, storage devices and electric vehicles, the concept of central generation has transformed to local distributed generation (DG). With this phenomenon reshaping the current perspective of distribution networks, the local generation and storage capacities, with their respective controllers, allow for these DG units to be grouped together to form single-phase microgrids most commonly referred to as residential microgrids. This thesis looks into the two key issues pertaining to residential microgrids i.e. accommodating multiple embedded generation and energy storage units while balancing the generation and loading in each phase to achieve overall three-phase system balance.\nA benchmark distribution system model is proposed in this thesis to study residential microgrids both in grid-connected and islanded modes. Limitations in existing distribution network models have been identified along with possible architectures for these residential microgrids. The configuration parameters of the benchmark model have been carefully selected after consultation with the London Hydro (local power utility in London, Ontario). Several case studies have been presented to show that the proposed benchmark model can be used to represent a particular architecture of the residential microgrids.\nMathematical foundations of balancing residential microgrids through back-to-back converters have been developed in this thesis, which lay the foundation stone of the subsequent contributions with regards to this thesis. An online toolkit is developed in LabVIEW from the derived mathematical formulations.\nTwo power management strategies for single-phase residential microgrids, namely intra-phase and inter-phase power management strategies have been proposed which cater for the coordinated control of these single-phase microgrids to balance generation and loading in all of the three-phases seen from a primary feeder.\nAn operational control strategy has been later studied for optimal selection of power surplus phase(s) to mitigate the deficit(s) in other phase(s). This allows the system to transfer power from the surplus phase(s) to power deficient ones to achieve an overall balance, despite diverse load demand profiles in each phase.\nAn experimental validation of the proposed control strategies has been carried out with laboratory-scale design and development of the back-to-back converter along side single-phase sources, loads and a control platform to mimic a typical residential microgrid. From the experimental results, it is concluded that phase imbalance can be mitigated by the transfer of surplus power from a phase to the power deficit phase.\nThis work on power balancing single-phase residential microgrids can potentially open up new areas of research in the field of microgrids, especially with an unprecedented growth of roof-top PV panels.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| 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 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».