electric vehicles effects on the power grid considering smart charging/discharging: montréal case study
Notice bibliographique
Résumé
Electric vehicles (EVs) are increasingly recognized for their potential to save energy, reduce pollution, and protect the environment. This makes the promotion and adoption of EVs crucial for decreasing our reliance on oil, enhancing energy security at national and regional levels, and supporting sustainable economic and social development. Acknowledging these benefits has led to a strategic focus on encouraging the widespread use of EVs. In this regard, countries around the world have begun to implement policies aimed at accelerating the adoption of EVs. These policies range from incentives for EV purchases to investments in charging infrastructure, reflecting a commitment to transition to cleaner forms of transportation. As a part of these efforts, the Government of Canada has introduced new regulations that establish mandatory Zero-emission vehicle (ZEV) sales targets for manufacturers and importers of new passenger cars, SUVs, and pickup trucks. These regulations require that a minimum of 20 percent of new vehicles sold in Canada must be zero-emission by 2026, escalating to at least 60 percent by 2030 and reaching 100 percent by 2035. In accordance with these new laws and policies, the province of Québec has set its own ambitious target of having two million EVs on the road of Québec by 2030. This goal has led to the need for this study to measure and analyze the impact of Plug-in Hybrid Electric Vehicle (PHEV) charging demand on both the current and future power network of Montréal, the largest city in the province of Québec. In this regard, this study considers the integration of Québec's ZEV policy on the city's grid and will evaluate how the expected growth in the number of PHEVs will affect the network's stability and efficiency. Therefore, a multi-objective problem has been presented in this research study to simultaneously maximize the benefits for PHEV owners while minimizing the power loss in the system for the current and future network of the city of Montréal. The proposed multi-objective problem is also developed using the Epsilon-Constraint technique, which facilitates solving the complex multi-objective function problem. In this regard, the load profiles of three different parts of the city of Montréal have been considered for specific reasons. The downtown area of Montréal has been chosen as it serves both commercial and residential purposes. To analyze the impact of PHEV charging in residential areas, Cote Saint Luc and Notre-Dame-de-Grâce have been included in the study, where both are considered primarily residential neighborhoods. Additionally, Montréal is well-known for its festivals and events, which led individuals to spend considerable time in the city for leisure. As a result, Quartier des Spectacles and the Old Port have been selected as essential areas where people gather during their leisure time. To address the above-mentioned issue and analyze the effect of PHEVs on the network of Montréal, two different phases and approaches were considered in this study: Immediate Charging, which only uses the Grid-to-Vehicle (G2V) charging strategy, and Smart Charging, which uses both G2V and Vehicle-to-Grid (V2G) strategies with the assistance of an EV aggregator. Additionally, to validate the effectiveness of the Smart Charging results, an alternative approach known as Basic V2G was implemented. This Basic V2G approach serves as a basic V2G concept to evaluate and verify the advantages of using the Smart Charging scenario.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,002 |
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 ».