Demographic and Geographic Region Definition in Energy System Modelling. A case study of Canada’s path to net zero greenhouse gas emissions by 2050 and the role of hydrogen
Notice bibliographique
Résumé
The urgency of reducing greenhouse gas emissions is greater now than ever, with the impacts of climate change becoming more apparent each year. Due to this, governments are setting ambitious targets such as reaching net zero GHG emissions by 2050, as announced by Canada in November of 2020. Within this context, the energy transition continues to gain momentum, as energy systems currently contribute to a large portion of these emissions. In order to support the energy transition, researchers, planners and policy makers alike are considering alternative solutions, such hydrogen, and are becoming increasingly reliant on energy system models in order to determine how the energy systems of the future should evolve. This thesis adapts an optimization based energy system model called EnergyScope in order to model potential pathways for the production and utilization of hydrogen within an energy system. Further, different methods of the definition of regions within energy system models are considered. The EnergyScope model is adapted from a model based on regions defined by political boundaries, to a model based on regions defined by geographic and demographic characteristics. A method for defining these regions and integrating them into the model is developed. These models are then used to assess how Canada could meet its goal of reaching net zero GHG emissions by 2050 within the energy sector, and what role hydrogen could play in this future energy system. The results highlight the importance of electrification in achieving a net zero energy system, indicating that the future system will be mainly based on renewable electricity generated by PV, wind and solar technologies. This will be used to fulfill the energy demand of the electricity sector, as well as the heating and transportation sectors, which will be mostly electrified. The results also indicate that hydrogen has a potential role to play in energy storage and heating in this net zero energy system, storing electricity when it is produced in excess and being used directly for heating (in place of electricity) when electricity generation is lower. The model indicates that hydrogen will likely be produced by emission free technologies such as natural gas pyrolysis and electrolysis, although uncertainty remains as these technologies are still maturing. Further, it is shown that the definition of regions used in energy system models based on demographic and geographic characteristics, rather than political boundaries, can provide additional insights particularly regarding the distribution of the potential of variable renewable technologies such as wind and solar, and how this corresponds to the distribution of demands and energy resource exchange networks.
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 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) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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) | 0,000 | 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 ».