A Distance Metric Based Approach for Analyzing, Assessing, and Strengthening EV Policy

Payal Vyankat Dahiwale;Zakir H. Rather;Indradip Mitra
{"title":"A Distance Metric Based Approach for Analyzing, Assessing, and Strengthening EV Policy","authors":"Payal Vyankat Dahiwale;Zakir H. Rather;Indradip Mitra","doi":"10.1109/TEMPR.2024.3454413","DOIUrl":null,"url":null,"abstract":"In realizing seamless mass adoption of electric vehicles (EVs), the government plays a vital role by framing and implementing various EV related policies. These policies, if framed adequately, play a key role in achieving electrification of transportation in States. The literature review suggests that there is a pressing need to develop a unified method to analyze the EV policy of a State and determine its effectiveness as well as key interventions to strengthen EV policy. Therefore, to determine the quality and the effectiveness of EV policies, a quantitative analysis of EV policies by using the Hamming distance and the L1 norm (Manhattan distance) has been proposed in this paper. The policies are analyzed based on essential interventions to promote and strengthen electric mobility. This paper proposes an L1 norm-based EV policy analysis that assigns a remoteness score to indicate the status of the existing EV policy and its implementation when compared to the ideal EV policy. The paper proposes an approach that is based on three methods to improve the remoteness score: cost of intervention implementation, benefit of the intervention to the EV ecosystem, and the number of move/steps that are required to reduce the remoteness score. The proposed approach as applied to various Indian State EV policies has identified the States whose EV policies have lower remoteness score, thereby highlighting the States having relatively better EV policies. The analysis of these methods for optimal intervention selection when implemented for various State EV policies shows that the intervention implementation cost-based method is the most economical one. This paper formulates a linear optimization problem with the objective of intervention-implementation cost minimization to develop an economical roadmap to reduce the remoteness score. Recommendations for EV policy makers and stakeholders using an optimization based quantitative analysis of EV policies in India are also presented in this paper.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"3 1","pages":"46-58"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Energy Markets, Policy and Regulation","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10664029/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In realizing seamless mass adoption of electric vehicles (EVs), the government plays a vital role by framing and implementing various EV related policies. These policies, if framed adequately, play a key role in achieving electrification of transportation in States. The literature review suggests that there is a pressing need to develop a unified method to analyze the EV policy of a State and determine its effectiveness as well as key interventions to strengthen EV policy. Therefore, to determine the quality and the effectiveness of EV policies, a quantitative analysis of EV policies by using the Hamming distance and the L1 norm (Manhattan distance) has been proposed in this paper. The policies are analyzed based on essential interventions to promote and strengthen electric mobility. This paper proposes an L1 norm-based EV policy analysis that assigns a remoteness score to indicate the status of the existing EV policy and its implementation when compared to the ideal EV policy. The paper proposes an approach that is based on three methods to improve the remoteness score: cost of intervention implementation, benefit of the intervention to the EV ecosystem, and the number of move/steps that are required to reduce the remoteness score. The proposed approach as applied to various Indian State EV policies has identified the States whose EV policies have lower remoteness score, thereby highlighting the States having relatively better EV policies. The analysis of these methods for optimal intervention selection when implemented for various State EV policies shows that the intervention implementation cost-based method is the most economical one. This paper formulates a linear optimization problem with the objective of intervention-implementation cost minimization to develop an economical roadmap to reduce the remoteness score. Recommendations for EV policy makers and stakeholders using an optimization based quantitative analysis of EV policies in India are also presented in this paper.
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信