Diffusion Of Electric Vehicles Research Articles

How can personal carbon trading be applied in electric vehicle subsidies? A Stackelberg game method in private vehicles

The withdrawal of purchase subsidy policy in China has already negatively affected the market proliferation of electric vehicles (EVs), and after the end of the withdrawal, personal carbon trading (PCT) is expected to become a subsidy policy system to stimulate EV market development from the consumption-side. Academics have verified the effectiveness of PCT subsidy for EV market development, but key issues including implementation details and recommendations are still in the research gap stage. This study establishes a three-level Stackelberg game model of government-supplier–consumer for a single product supply system of vehicles when using PCT to subsidize EVs, and the Nash equilibrium solution of the three-level game is the decision behavior under the optimal utility of three players. Then numerical experiments are conducted with actual data in Beijing to discuss the key issues in the implementation of PCT subsidy mechanism, including the setting of carbon prices and allocation of initial carbon credits, and verify the correctness of the game model. The main conclusions are as follows: 1) PCT has higher subsidy efficiency than purchase subsidy and saves more total government expenditure in the auto market, and the CO2 emission reduction effect of PCT is also better than purchase subsidy, and for 100 thousand newly increased vehicles, the former can achieve 300–400 t more CO2 emission reduction than the latter. 2) When the allocation of initial carbon credits adopts the Market Clearing Model, the supply and demand balance should be calculated separately for private vehicles, taxis and buses, and a differentiated carbon price should be adopted to ensure the fairness of the trading market. 3) The two initial carbon credit allocation models, Market Clearing and Financial Underwriting, can meet different development needs and achieve similar market diffusion effects for EVs. Under both models, the initial carbon credits allocated to EV owners will keep decreasing, and the appropriate increase in carbon price can still ensure high market demand for EVs. 4) The more the government pays attention to environmental pollution, the higher the market demand for EVs will be, and the government decision should keep raising the importance of environmental pollution effect to accelerate the diffusion of EVs. The research results can promote the application of PCT subsidy mechanism and further become a subsidy policy system on the consumption-side of the auto market, helping the transport industry to take the lead in achieving the goal of “carbon peak” and “carbon neutrality”.

Investigating Market Diffusion of Electric Vehicles with Experimental Design of Agent-Based Modeling Simulation

The transportation sector is recognized as one of the largest contributors to the problems of global warming and environmental pollution, and is responsible for a great deal of global energy consumption, which is heavily dependent upon scarce crude oil reserves. Different countries have adopted promotional policies to replace conventional internal combustion engine vehicles with electric vehicles as a means of mitigating global warming. Nevertheless, the current market share of eco-friendly vehicles remains stagnant in many parts of the world. This study aims to investigate the impact and relative importance of financial, technical, and political measures on the market penetration of electric vehicles using an agent-based simulation. More specifically, a series of agent-based simulation experiments is carried out following the statistical experimental design scheme to systematically assess the diffusion of electric vehicles. Affected by various factors and measures, the choice behavior of individual agents is modeled with a multinomial logit utility function of experimental factors. The simulated data are analyzed using different analysis methods, including full factorial analysis, response surface methodology, and support vector machine, in order to scrutinize the effects of different measures. It is advocated that factors affecting the choice of vehicle by individuals, including two-way interactions among various measures as well as policy measures such as purchase subsidies and tax breaks, have more significant effects on the widespread adoption of electric vehicles than do technical improvements in terms of battery charging times and driving mileage. This implies that the adoption of such measures needs to be carefully designed in order to account for potential interactions among individual measures as well as their main effects on the diffusion of electric vehicles.

Do I need to charge right now? Tailored choice architecture design can increase preferences for electric vehicle smart charging

The increasing diffusion of electric vehicles (EVs) can challenge the stability of distribution grids. Smart charging systems can reduce the stress of EV charging on the grid, but the potential of the technology depends on EV drivers' participation in smart charging schemes. To investigate this potential, we conducted an online randomised-controlled experiment with two waves (baseline and experimental phase, N = 222), in which we examined drivers' preferences for smart charging and tested a behavioral intervention to increase the number of smart charging choices. We translated state-of-charge (SoC) information from percentage of battery level into miles corresponding to the battery level and tailored information, i.e., the number of driving days covered by the actual SoC based on participants’ personal driving profiles. Participants preferred to use smart charging systems to decrease costs and to increase renewable energy use. However, they tended to overestimate the importance of the battery SoC when setting charging preferences. This overestimation was especially evident for participants who only drive short distances and may be lead to inefficient use of smart charging technology. Translating battery SoC into tailored information corrected for this bias and increased the number of smart charging choices. Our findings illustrate how behavioral interventions can be leveraged to attain energy transition goals.

Plug-in electric vehicle diffusion in California: Role of exposure to new technology at home and work

• Neighborhood effect plays an important role in plug-in electric vehicle diffusion. • Peer effect at the workplace has an important impact on the diffusion process. • Positive effect of charging infrastructure on PEV sales. • Targeted policies like Clean Car 4All can encourage PEV adoption. The market for plug-in electric vehicles (PEVs) --including both battery electric vehicles (BEVs) and plug-in hybrid vehicles (PHEVs)--has been rapidly growing in California for the past few years. Given the targets for PEV penetration in the state, it is important to have a better understanding of the pattern of technology diffusion and the factors that are driving the process. Using spatial analysis and Poisson count models we identify the importance of a neighborhood effect (at home locations) and a workplace effect (at commute destinations) in supporting the diffusion of PEV technology in California between 2014 and 2016. In the case of new BEV sales, we find that exposure to one additional BEV or PHEV within a 1-mile radius of a census block group centroid is associated with a 0.2% increase in BEV sales in the block group. Interestingly, for new PHEV sales- the neighborhood effect of BEV sales is negative, suggesting that enhanced exposure to this type of technology (which is differentiated in distinctive ways from PHEVs) may impact new PHEV sales through a substitution effect. Specifically, higher BEV concentration in an area can have an overall negative effect on new PHEV sales. While the neighborhood effect at residential locations is important, a workplace effect also has a notably important influence on new PEV sales. Both effects work in combination with socioeconomic, demographic, policy, and built environment factors in encouraging PEV adoption. These results, insightful not just for California but other regions in early phases of the PEV market, suggest that policymakers should consider targeted programs and investments that can attract a wider group of early adopters (in terms of sociodemographic characteristics and spatial location) to boost the impact of neighborhood and workplace effects on PEV sales.

A spatial agent-based joint model of electric vehicle and vehicle-to-grid adoption: A case of Beijing

The potential widespread adoption of Electric Vehicles (EVs) has received considerable attention across the globe. However, as a promising technology for both EVs and smart grid, Vehicle-to-Grid (V2G) tended to receive much less attention. This paper developed an agent-based joint EV and V2G model to simultaneously simulate how EVs and V2G might diffuse across space and over time, with empirical findings from a questionnaire survey in Beijing. In particular, random forest models were developed with the survey data to generate each agent’s preferences and attitudes towards EVs and V2G. The joint model also considered three typical levels of social influence, i.e., global influence, neighbor effect, and friendship effect, in the diffusion of EVs and V2G. Finally, the joint model was tested through several “what-if” scenarios, considering different V2G prices, EV/V2G advertisement intensities, and vehicle purchase restrictions. The survey results suggested that 67.7% of the respondents were familiar with EVs, but only 3.3% of them were familiar with V2G. However, over 70% of them would/might try V2G given that they had an EV. The model results suggested that the number of CV applicants was 6.19 times that of BEV applicants in 2030 in the baseline scenario, and only 27.8% of BEV users adopted V2G. Furthermore, V2G selling price, EV/V2G advertisement, and dedicated PHEV purchase permits were not very influential to the diffusion of V2G. The outcomes would be helpful for EV- and V2G-related stakeholders in policy making and technology investment.

Diffusion and benefits evaluation of electric vehicles under policy interventions based on a multiagent system dynamics model

Electric vehicle (EV) diffusion plays a vital role in transforming and upgrading China's automobile industry by ensuring energy security, improving air quality, and contributing to achieving the goal of carbon neutrality by 2060. EV diffusion is a complex dynamic system that involves various agent interactions. Nevertheless, previous research has rarely focused on the impact of different policies on EV diffusion under multiagent interactions and thus has not systematically evaluated its diffusion benefits. This paper establishes a multiagent system dynamics (SD) model to explore the impact of different policies on the diffusion and benefits of EVs. The results indicate that (1) EV diffusion is most significantly impacted by licence plate restrictions, following by charging pile construction subsidy, most sensitive to purchase subsidy policies, and least affected by government R&D subsidies. (2) Moreover, all four policies decrease EV energy benefits but positively impact the carbon emission reduction, health, and social benefits of EVs. The health benefits of EVs are the greatest, followed by the carbon emission reduction benefits. (3) The benefits of government subsidies to EV manufacturers, consumers, and charging infrastructure operators are positive. Finally, by integrating the development situation of China's EV industry, feasible policy suggestions are proposed for sustainable development.

The impact of electric vehicles on the future European electricity system – A scenario analysis

The future transformation of the European electricity system will be strongly influenced by both an ongoing integration of variable renewable energy sources (VREs) and an increased proliferation of electric vehicles (EVs). This combination will cause considerable uncertainty, especially since EV diffusion may greatly vary regarding both the spatio-temporal penetration pattern and the achievable flexibility level. Notably, power plant investment in the long run and dispatch in the short run will be affected. Hence, this paper assesses the impact of EV penetration on the integration of VREs and the costs of CO2 emission reduction as well as the necessary investments in controllable plant capacities under the consideration of frequency reserve and backup capacity requirements. Applying an extended European energy system model, we found that EVs with a high flexibility level may contribute tremendously to improved VRE integration, alleviating the number of necessary VRE investments to achieve emission-reduction goals. Simultaneously, overall system costs are reduced even though necessary investments in controllable plants, ensuring the abovementioned system stability needs, significantly increase. Policy makers should hence ensure sufficient incentives to both exploit the EVs’ potential and safeguard corresponding investments in controllable plants, which need to remain attractive even though full-load hours are decreasing.

The transition to electric mobility: opportunities for the automotive value chain in Argentina

The current transition from internal combustion engine vehicles to electric vehicles opens windows of opportunity for the repositioning of firms and countries in global and regional automotive value chains. The objective of this paper is to study these opportunities posed for the automotive chain in Argentina. The main results show that Argentina lags behind in the production and diffusion of electric vehicles and has a low deployment of the charging infrastructure. However, this transition would be an opportunity for Argentina to reposition itself in the regional automotive value chains; and its growing specialisation in pickups could position it in the nascent electric pickup market, without large, consolidated players. At the same time, there are opportunities to increase the national integration of parts and components of the electric powertrain and reduce the high incidence of imports of auto parts.

Investigating Market Diffusion of Electric Vehicles with Experimental Design of Agent-Based Modeling Simulation

Investigating Market Diffusion of Electric Vehicles with Experimental Design of Agent-Based Modeling Simulation

Prototype of Urban-Scale Battery Usage Simulator to Examine Promotion of Electric Vehicles

In recent years, electric vehicle has been expected to spread, but due to various factors such as limitations on the vehicle side caused by technical specifications of batteries and lack of charging infrastructure, the spread of electric vehicle in society has not progressed. Therefore, this study aims to examine the possibility of electric vehicle diffusion methods that take both vehicle and infrastructure into account by focusing on battery usage. In this presentation, we report on a development of an urban scale battery usage simulator that uses battery installation and replacement methods, technical specifications such as the type and size of electric vehicle vehicles, and user behavior such as vehicle and charging behavior as variables.

What's Blocking Fuel-Cell Electric Vehicle Diffusion? Evidence from Germany, Japan and California

What's Blocking Fuel-Cell Electric Vehicle Diffusion? Evidence from Germany, Japan and California

Wrought and Cast Aluminum Flows in China in the Context of Electric Vehicle Diffusion and Automotive Lightweighting

Wrought and Cast Aluminum Flows in China in the Context of Electric Vehicle Diffusion and Automotive Lightweighting

Factors Affecting Electric Vehicles Diffusion Among Private Users:Empirical Evidence from Italy

Factors Affecting Electric Vehicles Diffusion Among Private Users:Empirical Evidence from Italy

What determines consumers' acceptance of electric vehicles: A survey in Shanghai, China

In China, although the number of registered electric vehicles (EVs) has recently risen, the market share of EVs is not comparable to that of conventional internal combustion engine vehicles (ICEVs). To identify the determinants of EV acceptance, this study performs a questionnaire survey in Shanghai, the economic center of China and one of the earliest pilot cities for promoting EVs, using the structural equation model (SEM) to investigate the influences of five external factors and eight demographic characteristics on consumers' EV purchases. In particular, we examine the peer effect of consumers to explore the impact of consumer interaction on EV diffusion. Although rarely considered in previous studies, peer effects have a significant impact on the diffusion of new products. In addition, we conduct a heterogeneity analysis between consumers who have bought EVs and those who have not. The results demonstrate that the main buyer of EVs in Shanghai is younger, mainly between 31 and 40 years old. Consumers with high income, high education and living in the city center are more willing to choose EVs, while families with large family members prefer not to buy EVs. Consumers who have not bought EVs are more concerned about EV performance. Consumers who have already purchased EVs pay more attention to the availability of charging facilities and government policies related to EVs, especially the free license plate policy in Shanghai. Particularly, peer effects play a significant role in consumers' EV purchase decisions of the two types of consumers, which proves that the information exchange between peers has a great influence on their purchase decisions. This study provides evidence for the catalytic role of peer effects in consumers' purchasing of EVs. The outcomes of this paper provide evidence for governments and enterprises on the importance of the role of peer effects and consumer heterogeneity in EV diffusion.

The Role of Government in the Market for Electric Vehicles: Evidence from China

AbstractGovernments in many countries have offered various incentives to promote the diffusion of electric vehicles (EVs). This study examines the effectiveness of various policy measures that underlie the rapid development of the EV market in China, by far the world's largest such market. The analysis is based on detailed data on EV sales, local and central government incentive programs, and charging stations in 150 cities from 2015 to 2018. The empirical framework addresses the potential endogeneity of key variables, such as local policies and charging infrastructure, by using a city‐border‐regression design and instrumental variable approach. We find that consumer subsidies for vehicle purchases accounted for more than half of EV sales in China. Nevertheless, investments in charging infrastructure were much more cost‐effective than consumer subsidies. An inexpensive policy that merely provided EVs with a distinctive, green license plate was strikingly effective. These findings demonstrate the varying efficacy of different policy instruments and highlight the critical role of the government in promoting clean technologies.

A coordinated optimal programming scheme for an electric vehicle fleet in the residential sector

The development of intelligent strategies to manage electric vehicle charging process is the key for fostering a proper diffusion of electric vehicles at customer premises. The presence of renewable generation and the exploitation of vehicle-to-grid can enhance this process. In this paper, two procedures are proposed for optimizing electric vehicle charging strategies, for an aggregation of consumers, with the objectives of load profile levelling and total cost minimization, in the presence of possible realistic diffusion of photovoltaic systems and electric vehicles. Moreover, the best compromise between the two objectives is evaluated by determining techno-economic merit indicators. The procedures are applied to a realistic case study in the UK, considering an aggregator managing a group of residential customers in a low-voltage distribution network, where multiple tariff schemes are assessed. • Realistic EV diffusion in residential districts with V2G charging points is analysed. • Alternative procedures for load levelling and cost reduction are proposed. • Operation performances are compared through merit indicators with weighting factor.

Inflated lives and a clean tech privilege in Washington State: Policy amidst spatialized affluence

In this study, we analyze policy and the socio-spatial distribution of clean technology privilege—electric vehicles (EVs)—in Washington State. We examine EV penetration in relation to zip code variables like social demographics and population density. Data was acquired from the US Census and Washington State’s vehicle registry (N = 576). After regression and geographic analyses, we find that median income, an Inflated Life Proxy (ILP), and education have the highest associations with EV concentrations. The ILP was constructed by dividing zip code median home values by median incomes. We also find associations between EV penetration and the distribution of broadband internet. As the highest EV adoption shares are found in areas of the highly educated and affluent—a clean tech privilege—we argue that, despite years of state and federal incentives, EV diffusion in Washington State has not progressed beyond early adoption. As the association between greater household income and greenhouse gas emissions is well established, we urge decision makers toward more progressive economic policies—consumption, wealth, and income taxes—in order to direct civil society towards greater economic moderation and equality, generally. If only consumers with a clean tech privilege are adopting EVs, then current emission reduction strategies may be annulled by the otherwise high carbon lifestyles of the affluent.

Analysis on the electric vehicle with a hybrid storage system and the use of Superconducting magnetic energy storage (SMES)

Given the current load and power density limitations in electric vehicle (EV) storage systems, it is necessary to study hybrid and control systems in order to optimize their performance and present themselves as a real alternative to internal combustion engine (ICE) vehicles. This implies the development of legislation and specific regulations that enable the research and development of these storage and management systems for hybrid systems. The research presented here aims to analyze the implementation of the SMES (Superconducting Magnetic Energy Storage) energy storage system for the future of electric vehicles. To do this, the need for a hybrid storage system has been taken into account, with several regulatory options, such as the reduction of rates or the promotion of private investments, which allow the technological development of EVs. What is sought is to achieve the market share proposed by the different countries to reduce Greenhouse Gases (GHG), according to their objectives. This approach must be taken from the legislative and regulatory perspective, specific to EVs and charging points, of several countries or regions with different cultures, management models and implementation potential, such as the United States of America (USA), Europe and China. This analysis is associated with the economic study of costs that this storage system may involve in the implementation of EVs to replace ICE vehicles, resulting in possible economic benefits as well as the environmental benefits of the use of EVs. In this analysis, the current high cost of using a hybrid system of these characteristics can be observed with the comparison of three EVs, as well as current data on GHG emissions produced by transport. All this leads to a series of advantages and disadvantages that must be taken into account in order to achieve the objectives that countries have in the coming decades of EV diffusion.

Public charging infrastructure and electric vehicles in Norway

We study whether public charging infrastructure drives battery electric vehicle adoption. Our analysis is based on granular, annual information on the location of public charging infrastructure and the battery electric vehicle ownership rate across 356 Norwegian LAU-2 municipalities between 2009 and 2019. We focus on areas in which the first public charging infrastructure was installed in this time period. In these mostly rural areas, the establishment of a first public charging station initiated adoption. We find, on average, an increase of the local electric vehicle ownership rate by 1.5 percentage points or 200% over 5 years. Our results are robust to anticipatory effects. They also remain unaffected from different treatment thresholds: the median number of public chargers in a municipality between 2009 and 2019 or the median density of public charging points per 1000 inhabitants in the same time frame. While we cannot fully rule out reverse effects, we identify public charging infrastructure to serve as a stimulus to the diffusion of battery electric vehicles.

A multi-level optimization model of infrastructure-dependent technology adoption: Overcoming the chicken-and-egg problem

Policymakers seeking to promote the diffusion of infrastructure-dependent technologies are often confronted with the “chicken-and-egg” problem: consumers are reluctant to adopt the technology without adequate infrastructure available, and firms are reluctant to invest in infrastructure without a sufficient number of adopters. This chicken-and-egg problem can hinder the diffusion of new technologies and prolong the timeframe over which existing technological systems remain locked-in. In this paper, we formulate a stylized model of technology policy decision-making from the perspective of a policymaker who seeks to stimulate the market penetration of an infrastructure-dependent technology. Our model is a multi-level optimization problem in which a policymaker (first level) maximizes net social benefits by setting the levels of two incentives: a subsidy for a profit-maximizing firm (in equilibrium with two other firms, the second level) to invest in infrastructure that raises the benefit of adoption to consumers, and a direct subsidy for consumers to adopt the technology (third level). Under certain assumptions about functional forms, we solve the full multi-level problem analytically through backward induction and derive closed-form expressions for the policymaker’s optimal subsidy levels. Then, we present a case study on policies to promote battery electric vehicle (BEV) diffusion. Our results reveal three main insights: (1) the optimal policy portfolio often subsidizes charging infrastructure more than BEV purchases, (2) infrastructure and adoption subsidies tend to be substitutes rather than complements, and (3) an increase in the marginal social benefit of BEV adoption shifts the optimal policy away from infrastructure subsidies and toward BEV subsidies.