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

Payal Vyankat Dahiwale;Zakir H. Rather;Indradip Mitra
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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.
基于距离度量的电动汽车政策分析、评估和强化方法
为了实现电动汽车的无缝普及,政府通过制定和实施各种电动汽车相关政策发挥着至关重要的作用。这些政策如果框架适当,将在各国实现运输电气化方面发挥关键作用。文献综述表明,迫切需要建立一种统一的方法来分析国家的电动汽车政策,确定其有效性,以及加强电动汽车政策的关键干预措施。因此,为了确定电动汽车政策的质量和有效性,本文提出了使用汉明距离和L1范数(曼哈顿距离)对电动汽车政策进行定量分析的方法。根据促进和加强电动交通的基本干预措施,分析了政策。本文提出了一种基于L1规范的电动汽车策略分析,该分析分配了一个远程分数,以表明现有电动汽车策略的状态及其与理想电动汽车策略的实施情况。本文提出了一种基于三种方法来提高远程评分的方法:实施干预的成本,干预对电动汽车生态系统的好处,以及降低远程评分所需的移动/步数。该方法应用于印度各邦电动汽车政策,确定了电动汽车政策偏远程度较低的邦,从而突出了电动汽车政策相对较好的邦。对各种国家电动汽车政策实施干预的最优选择方法进行了分析,结果表明基于成本的干预实施方法是最经济的干预实施方法。本文以干预实施成本最小化为目标,建立了一个线性优化问题,以制定降低远程评分的经济路线图。本文还对印度电动汽车政策进行了基于优化的定量分析,为电动汽车政策制定者和利益相关者提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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