{"title":"Impact of Large-Scale Electric Vehicles’ Promotion in Thailand Considering Energy Mix, Peak Load, and Greenhouse Gas Emissions","authors":"Ashok Paudel, Watcharakorn Pinthurat, Boonruang Marungsri","doi":"10.3390/smartcities6050118","DOIUrl":null,"url":null,"abstract":"Thailand’s policies are in accord with the global drive to electrify transportation vehicle fleets due to climate concerns. This dedication is evident through its adoption of the 30@30 initiative and the planned ban on new internal combustion (IC) engine vehicles by 2035, showcasing a strong commitment. The objective of this study was to utilize the Low Emission Analysis Platform (LEAP) software to model the transition possibilities for electric vehicle (EV). Emphasis was placed on the future of the light-duty vehicle (LDV) sector, encompassing the energy sources, electric power demands, and greenhouse gas (GHG) emissions. Two scenarios were evaluated: one involving rapid economic growth and the other characterized by a more-gradual expansion. The former projection foresees 382 vehicles per thousand people by 2040, while the latter estimate envisions 338 vehicles. In the scenario of high growth, the vehicle stock could surge by 70% (27-million), whereas in the case of low growth, it might experience a 47% rise (23.3-million) compared to the base year (15.8 million). The increased adoption of EVs will lead to a decrease in energy demand owing to improved fuel efficiency. Nonetheless, even in the most-extreme EV scenarios, the proportion of electricity in the energy mix will remain below one-third. While GHG emissions will decrease, there is potential for even greater emission control through the enforcement of stricter emission standards. Significant EV adoption could potentially stress power grids, and the demand for charging might give rise to related challenges. The deployment of public fast charging infrastructure could provide a solution by evenly distributing the load across the day. In the most-rapid EV penetration scenario, a public charging program could cap the demand at 9300 MW, contrasting with the 21,000 MW demand for home charging. Therefore, a recommended approach involves devising an optimal strategy that considers EV adoption, a tariff structure with incentives, and the preparedness of the infrastructure.","PeriodicalId":34482,"journal":{"name":"Smart Cities","volume":"41 1","pages":"0"},"PeriodicalIF":7.0000,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Cities","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/smartcities6050118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Thailand’s policies are in accord with the global drive to electrify transportation vehicle fleets due to climate concerns. This dedication is evident through its adoption of the 30@30 initiative and the planned ban on new internal combustion (IC) engine vehicles by 2035, showcasing a strong commitment. The objective of this study was to utilize the Low Emission Analysis Platform (LEAP) software to model the transition possibilities for electric vehicle (EV). Emphasis was placed on the future of the light-duty vehicle (LDV) sector, encompassing the energy sources, electric power demands, and greenhouse gas (GHG) emissions. Two scenarios were evaluated: one involving rapid economic growth and the other characterized by a more-gradual expansion. The former projection foresees 382 vehicles per thousand people by 2040, while the latter estimate envisions 338 vehicles. In the scenario of high growth, the vehicle stock could surge by 70% (27-million), whereas in the case of low growth, it might experience a 47% rise (23.3-million) compared to the base year (15.8 million). The increased adoption of EVs will lead to a decrease in energy demand owing to improved fuel efficiency. Nonetheless, even in the most-extreme EV scenarios, the proportion of electricity in the energy mix will remain below one-third. While GHG emissions will decrease, there is potential for even greater emission control through the enforcement of stricter emission standards. Significant EV adoption could potentially stress power grids, and the demand for charging might give rise to related challenges. The deployment of public fast charging infrastructure could provide a solution by evenly distributing the load across the day. In the most-rapid EV penetration scenario, a public charging program could cap the demand at 9300 MW, contrasting with the 21,000 MW demand for home charging. Therefore, a recommended approach involves devising an optimal strategy that considers EV adoption, a tariff structure with incentives, and the preparedness of the infrastructure.
期刊介绍:
Smart Cities (ISSN 2624-6511) provides an advanced forum for the dissemination of information on the science and technology of smart cities, publishing reviews, regular research papers (articles) and communications in all areas of research concerning smart cities. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible, with no restriction on the maximum length of the papers published so that all experimental results can be reproduced.