The Development of a Framework for Modelling Greenhouse Gas Mitigation Scenarios in the Electricity Generation Sector
Notice bibliographique
Résumé
Low- or zero-emitting alternative sources of energy have become widely sought for reducing greenhouse gas (GHG) emissions globally. Specifically, in the electricity generation sector, governments, utilities, regulators, and institutions have announced and implemented integrated policy measures such as renewable electricity generation targets, incentives, and efficiency standards for climate change mitigation. However, the associated constraints of recoverable resource viability, public acceptability, and high investment costs, along with limited generation output of alternative energy technologies compared to fossil fuel technologies, could make a low-emission electricity generation mix uneconomical to pursue. Therefore, it is necessary to quantitatively evaluate the greenhouse gas mitigation possible and the associated abatement costs from different integrated alternative energy penetration scenarios in an electricity generation mix in order to make informed policy decisions. The Long-range Energy Alternative Planning (LEAP) software was used to model the power generation sector over a study period of 41 years (2010-2050). Alberta, a Western Canadian province, was selected to evaluate the environmental and policy implications of the foregoing. This study assessed the comparative GHG mitigation in terms of dollar per tonne avoided and cumulative GHG emissions that could result from the adoption of different alternative energy penetration scenarios in which fossil fuels are replaced in an electricity generation mix in the medium term (to the year 2030) and long term (to 2050) using LEAP. Pathways for increasing the renewable share of electricity generation and associated GHG mitigation possible were investigated. The business-as-usual (BAU) scenario and 18 alternative scenarios were developed, simulating situations in which high-emission baseload coal-fired power plants would be retired and replaced by gas-fired power plants for baseload generation, and zero- or low-emission alternatives such as biomass hydro, solar, wind, geothermal, and nuclear are introduced into the generation mix to replace at least two-thirds of retired coal capacity by 2030. Over the study period, the results show that a GHG mitigation potential of 44% to 60% below 2014 reported emissions of 48.9 Mt CO2 eq. from the electricity generation sector may be achieved by the year 2030. A 30% renewable capacity target would increase the renewable electricity production share from the current 10% to 22% by 2030. The GHG abatement costs of the alternative scenarios range from −$5/t CO2 eq. to $820/t CO2 eq. compared to the BAU by 2030. By 2050, about 42% to 65% GHG mitigation potential may be achieved with scenario abatement costs of −$13/t CO2 eq. to 214/t CO2 eq. compared to the BAU. The outcomes of this study offer insights into the selection of alternative energy penetration pathways for a lower GHG emission electricity generation mix in Alberta.
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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) | 0,000 | 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) | 0,000 | 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 ».