Integrated Optimization of Location, Design, and Operation of Renewable Energy Systems for Urban Microgrids
Notice bibliographique
Résumé
The building sector of urban areas plays a crucial role in carbon emissions and climate change. Distributed generation using clean energies could help to reduce emissions. Furthermore, urban microgrids increase the reliability of power supply since most of the power outages are created in the grid distribution system and transmission lines. However, a cost-effective design and operation of an urban microgrid poses challenges, such as limited space for installing the renewable components, especially in populated areas, the uncertainty of renewable resources, and the resiliency of the designed microgrid in case of not having access to the central grid. Therefore, this thesis was initiated with the objective of developing a comprehensive method for the efficient design of an urban microgrid. The developed framework consists of three main modules. The first module aims at designing an energy system for a community microgrid by sizing and finding the optimum configuration of the energy system. To resolve the spatial issue problem in urban areas, regional renewable generation is proposed in this research where clean energy is produced outside of the populated area as a virtual power plant in relation to the microgrid. A mapping model is also developed to select the best location for installing components outside the microgrid. The mapping model is connected with the optimization model to automatically generate the best configuration and location of regional generation based on several aspects of each zone. The second module deals with renewable resources and electrical load demand uncertainties and tries to reduce them by forecasting strategies. Since renewable resources such as solar irradiance and wind speed are not predictable using just historical data, hybridized numeric weather prediction (NWP) and deep learning models are offered to tackle the drawback. The last module proposes a solution to ensure resilience against power supply failures in electricity grids caused by extreme weather conditions, unavailability of generation capacities, and transmission components problems. \nThe discussed models were applied to one of Concordia University's largest buildings in downtown Montreal, Canada. The results show a significant improvement in the environmental aspect of the regional generation if the existing gas boiler would be substituted by electric boilers and heat pumps (using generated renewable electricity outside of microgrid), preventing emissions of about 4233 tons CO2 and 5.3 tons NOX per year. Using a proposed tariff structure beneficial to both the customer and utility, the resulting levelized cost of energy is about 5.3 Cents per kilowatt hour, i.e., lower than the current rate of about 6 Cents per kWh. Using the second module’s proposed hybrid models for renewable resources and electrical load demand prediction of the case study was also helpful by considerably bringing down the error. Finally, operation dispatch scenarios are developed to reinforce the system’s resiliency in severe conditions for the case study in the third module. A mixed-integer linear programming (MILP) approach is employed to identify global optimum dispatch solutions based on the next 48 h plans for different seasons to formulate a whole-year operational model. The results show that the loss of power supply probability (LPSP), as an indicator of resiliency, could be lowered to near zero while minimizing operational cost using the proposed optimal load (derived from critical load).
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 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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».