Life cycle assessment of electricity delivery systems: Attributional and Consequential approaches
Notice bibliographique
Résumé
The transition towards low carbon electricity generation can be guided by investigating the economic and environmental consequences of policy decisions. However, there is limited information on greenhouse gas (GHG) emissions, energy footprints, and changes in production cost under different policy constraints for emerging sustainable energy generation systems. This thesis, therefore, explores the environmental and economic implications of transitioning to a low carbon electricity generation system through a life cycle approach. Large-scale solar power plants have captured the attention of energy policymakers and industrial stakeholders globally because they can contribute to the long-term plan to reduce the impacts of climate change related to conventional fossil fuel power plants. In this study, we developed a comprehensive bottom-up life cycle assessment model to evaluate the emissions and energy profiles of large-scale solar photovoltaic systems. A case study for a fossil fuel-based energy jurisdiction, Alberta, a western province in Canada, was conducted. We also investigated the potential to use such an energy system to provide consistent electricity supply to the grid compared to peak load options. The results show life cycle GHG emissions of 60.21-79.61 g CO2eq/kWh, a net energy ratio (total energy output divided by total fossil fuel consumed over the lifecycle) of 7.48-10.04, and an energy payback time (time required to regain the invested energy) of 2.73-3.00 years. The system was integrated with lithium-ion energy storage for a consistent electricity supply over a period. The corresponding results are 155.25-220.61 g CO2eq/kWh, an NER of 2.63-3.61, and a payback time of 7.01-9.45 years. More than 60% of the energy consumed is in upstream manufacturing processes. We also developed a novel framework to evaluate the long-term environmental consequences of marginal changes in electricity generation that result from policy decisions in fossil fuel-dominant jurisdictions. The framework integrates market penetration, long-term energy demand and supply modeling, and marginal cost and emissions analyses. A case study for Alberta was conducted. Based on the province’s specific energy generation resources and its policy initiatives, we created 9 scenarios investigate the effects of renewable energy penetration under competitive market conditions (no renewable targets), regulations to ensure minimum production from renewables, improved storage capabilities, and GHG emission targets. With the Long-range Energy Alternatives Planning (LEAP) framework, we developed an energy generation model to calculate probable future electricity mixes, generation costs, and the resulting GHG emissions. The marginal changes in energy generation and GHG emissions were quantified for each scenario to incorporate different policy decisions and market effects. We determined that in Alberta combined cycle power plants and wind energy are the key marginal suppliers of electricity in the transition to a cleaner grid. The effects of adding energy storage to the grid along with renewable energy systems, replacing natural gas with renewable energy, and setting more aggressive GHG emission reduction targets than current policies require were also investigated. The information provided in this thesis would help concerned entities in formulating policies and making investments in the electricity sector.
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 | 0,007 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».