Home Charging Research Articles

How, where, and when to charge electric vehicles – net-zero energy system implications and policy recommendations

A coordinated Charging Infrastructure (CI) strategy could accelerate the adoption of Battery Electric Vehicles (BEVs). Policymakers need to understand the tradeoffs between several types of CI developments. To support decision-makers, we apply the Swiss TIMES Energy system Model, which we extended with heterogeneous consumer segments with four trip types and several CI options. The novelty of this work lies in the interplay of such method advancements, representing BEV charging options with various CI types that can be accessed based on their location type at an hourly intraday temporal resolution. In explorative scenario analyses, we evaluate the effects of CI on car fleet deployment and their energy system implications in achieving net-zero CO2 emissions in Switzerland by 2050. Our analysis shows that the BEV share makes up 39%–77% of the fleet by 2050, and each BEV needs about 5 kW total charging capacity, split into 1.6–2.6 BEVs per private charger and 18–25 BEVs per public charger. Providing overnight charging access through private home chargers or public chargers in residential areas facilitates a 12%–20% increased BEV penetration compared to the reference scenario. For consumers without private home charging, improved public CI in non-residential areas increases BEV uptake by 24%. While low-power slow CI is cost-effective at home, high-power fast CI in commercial areas supports integration of solar PV. We highlight the need for coordinated CI policies and provide a variety of policy options based on our analysis and international insights.

The Impact of Electric Vehicle Charging Stations on Consumers

New York currently has an inadequate supply of electric vehicle (EV) charging stations for drivers, despite the considerable efforts made by the local and national government to encourage the environmental benefits of EV usage. This study investigates the extent to which the scarcity of charging stations is inhibiting the widespread adoption of EVs on Long Island. A survey was conducted with a representative sample of the Long Island population to analyze which individuals were impacted most significantly. The findings suggest that the charging process, including cost and time, was not the problem. Rather, those without access to home charging and individuals who travel long distances were impacted the most. To remedy the situation, New York policy makers need to allocate more resources towards the expansion of the charging network and enhance consumers’ knowledge about the environmental benefits of EVs.

Smart home charging of electric vehicles using a digital platform

As the penetration of electric vehicles (EVs) grows, it is important to understand the implications of home charging technologies for grid operations and for the budget of users. We conduct an empirical study analyzing data on 438 EVs over a period of 3,687 consecutive hours, collected by an energy aggregator which operates a digital platform. We first develop an optimization model to compute an optimal schedule of charging for all EVs in the dataset at minimum cost. Then, we compare the realizations against this optimal solution, distinguishing householders who use a smart charging functionality of the digital platform from those who do not use it. Our findings indicate that the smart charging behaviour conduces to better results, and close to the optimal solution. The non-users tend to start charging as soon as they plug-in their EVs, often at peak consumption times. In contrast, the smart charging strategy usually shifts the charging schedules towards times where the consumption is cheaper and the grid is less congested, facilitating a higher load factor and lower power losses. These results highlight the positive role of energy aggregators and digital platforms in coordinating users to lower the cost and enhance efficiency of energy consumption.

Electric vehicle community charging hubs in multi-unit dwellings: Scheduling and techno-economic assessment

Democratizing access to charging infrastructure is a prerequisite for equitable electric vehicle (EV) adoption and use. Residential EV charging is the most prevalent and convenient option. However, multi-unit dwelling (MUD) residents have limited access to home charging, leading to higher operating costs and less flexibility. We introduce the concept of community charging hubs for shared charger use at MUDs. Our model minimizes the charging hub’s total waiting time. We measure the charging hub’s performance and evaluate the levelized cost of charging through a techno-economic assessment in Chicago, IL, New York City, NY, and Los Angeles, CA. We uncover trade-offs between the charging hub’s performance and its levelized cost of charging. Installing direct current fast charging stations costs more than adding level-2 stations but significantly reduces waiting times. The cost and performance metrics of small, medium, and large charging hubs and their average power profiles are presented for various hub configurations.

Estimating the electric vehicle charging demand of multi-unit dwelling residents in the United States

Early battery electric vehicle (EV) adopters can access home chargers for reliable charging. As the EV market grows, residents of multi-unit dwellings (MUDs) may face barriers in owning EVs and charging them without garage or parking availability. To investigate the mechanisms that can bridge existing disparities in home charging and station deployment, we characterized the travel behavior of MUD residents and estimated their EV residential charging demand. This study classifies the travel patterns of MUD residents by fusing trip diary data from the National Household Travel Survey and housing features from the American Housing Survey. A hierarchical agglomerative clustering method was used to cluster apartment complex residents’ travel profiles, considering attributes such as dwell time, daily vehicle miles traveled (VMT), income, and their residences’ US census division. We propose a charging decision model to determine the charging station placement demand in MUDs and the charging energy volume expected to be consumed, assuming that MUD drivers universally operate EVs in urban communities. Numerical experiments were conducted to gain insight into the charging demand of MUD residents in the US. We found that charging availability is indispensable for households that set out to meet 80% state of charge by the end of the day. When maintaining a 20% comfortable state of charge the entire day, the higher the VMT are, the greater the share of charging demand and the greater the energy use in MUD chargers. The upper-income group requires a greater share of MUD charging and greater daily kWh charged because of more VMT.

Do plug-in hybrid adopters switch to battery electric vehicles (and vice versa)?

Plug-in electric vehicle (PEV) adopters, which include owners of battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), have the choice to replace their vehicle with a BEV, PHEV, or conventional vehicle. These replacement choices are important to consider since they can impact PEV market growth. We investigate factors associated with the choice to replace a BEV or a PHEV with a PHEV, BEV, or conventional vehicle using survey responses from 1,446 PEV adopters. Most BEV adopters’ replacement choices are a newer BEV, for around 1/10th the replacement is a PHEV, and around ¼ replace their BEV with a conventional vehicle. PHEV adopters’ replacement choices are split more evenly between BEVs, PHEVs, or conventional vehicles. Replacement choices are correlated with vehicle attributes (e.g., range), satisfaction with vehicle attributes (e.g., charging convenience), home charging access, gas price, demographics, and attitudes toward technology, the environment and travel.

A Techno-Economic Assessment of a Second-Life Battery and Photovoltaics Hybrid Power Source for Sustainable Electric Vehicle Home Charging

This study discusses the use of a retired battery from an electric vehicle for stationary energy storage electric vehicle charging in a residential household. This research provides a novel in-depth examination of the processes that may be necessary to investigate the life loss of a battery, whether new or used. The main contribution is to promote the feasibility of the application from both a technical and economic point of view. The semi-empirical models are then utilized to analyze the life fading that is used in economic studies. In terms of lower initial investment costs for the battery and solar photovoltaics, the numerical calculation demonstrates that the used second-life battery with a DOD of 85% has more advantages over a new battery in the same condition. Additionally, compared to a new battery, a second-life battery gradually loses life and benefits from recycling after a projected 10-year lifespan. These results support the feasibility of the project. A discussion of project hurdles is included in which the hybrid converter modification may be achieved. Policymakers are encouraged to keep this valuable scheme in mind for the sake of margin profit and environmental preservation.

Evaluation of Distinct EV Scheduling at Residential Charging Points in an Unbalanced Power Distribution System

Electric vehicles (EVs) have significant potential and sustainability in the future transportation sector due to their less pollution and low operating cost. The uncoordinated charging of these EVs may push the power delivery system towards lower performance and even at the risk of damaging the power system equipment. The proper scheduling and coordination of EVs with the system may lessen the negative impact. In this paper, a multi-objective scheduling approach for individual candidate-based EVs is proposed to relieve the distress in power delivery in the best possible way. Minimization of average demand deviation and system unbalance reduction are selected as the objectives to restore the power delivery performance. The proposed approach has been verified on a realistic three-phase power distribution infrastructure. A simple linear regression model is employed to predict the near future number of EVs in the test region. An optimizitaion algorithm based on particle swarm optimization (PSO) technique is operated to find the finest solution satisfying EV charging constraints. The stochastic nature of load demands at the node points of the test network is analyzed with the help of a probabilistic demand model and it is further incorporated into the optimization framework. It is possible to reduce the system’s average demand deviation and unbalance level by 53.74% and 51.36%, respectively, with the proposed EV scheduling approach. A comparative study with the existing methods further claims the efficacy of the proposed approach. HIGHLIGHTS Framework for home charging schedule of distinct EVs Compliance with multi-objective power supply efficiency Probabilistic modeling of load demand from real collected data Optimization-driven solution for a test case in Mysore city in India

Statistical Analysis of Electric Vehicle Charging Based on AC Slow Chargers

Regarding DC fast chargers, various studies, such as the charge scheduling, have been conducted. On the other hand, research on AC slow chargers has rarely been conducted due to the predictable and simple usage pattern. Despite the long charging times of AC slow chargers, which use the existing electric outlets with relatively low supplied power, these chargers are suitable for daily home charging of electric vehicles (EVs) during the night. Due to their low installation costs, they are likely to be the dominant type of charging equipment. In this paper, the EV charging process based on AC slow chargers, which supply a maximum power of 3 kW from an AC 220 V outlet, is analyzed by constructing a simple charging model. The charging time and fees are statistically derived and investigated. Furthermore, power load curves for charging EVs with the 3 kW charger are observed. From the statistical analyses, we conclude that daily charging of EVs can be an appropriate scenario in using the AC slow chargers, and the power load can be spread without employing any demand response schemes.

Preferences for zero-emission vehicle attributes: Comparing early adopters with mainstream consumers in California

Ambitious zero-emission vehicle (ZEV) adoption goals have been proposed to decarbonize the transportation sector, while the current market share pales in comparison. Although the distinct socio-economic characteristics of ZEV early adopters relative to mainstream car buyers are well understood, the two groups' preferences for ZEV attributes are not clear. This knowledge gap hinders the development of effective policies to achieve mass ZEV penetration goals. This paper examines consumers’ preferences and willingness to pay for ZEV attributes based on 755 early adopters and 3493 mainstream consumers from the 2019 California vehicle survey data. Results show that early adopters are more sensitive to battery range, acceleration performance, home charging availability, and high occupancy vehicle lane access, while mainstream consumers attach greater importance to cost attributes (e.g., fuel and maintenance costs) and charging time. Moreover, the effects of monetary incentives are found to be significant for both groups, whereas neither early adopters nor mainstream consumers value the availability of public charging stations. The findings of this study inform targeted ZEV policymaking and marketing strategies in different adoption stages.

Assessing the willingness of Australian households for adopting home charging stations for electric vehicles

The objective of this study is to understand what factors drive household decisions to install electric vehicle charging infrastructure at home. To this end, we administrated an online questionnaire to 1,199 households drawn from across the state of New South Wales in Australia, who were asked to complete one of two discrete choice experiments (DCEs). The DCEs were customized based upon the type of property the recruited respondents reside in, with this being either a separate private dwelling (i.e., house) or a house/apartment belonging to a building complex. A Logit Mixed Logit model (Train, 2016), a non-parametric version of the traditional random effects discrete choice model, is used to analyse the data obtained from the two DCEs. The empirical findings suggest that both sampled populations positively value the opportunity to endow their property with EV home charging points, with those who live within apartment buildings clearly preferring having access to private charging as opposed to communal charging.

The impact of charging time of electric vehicle battery to costumer willingness to purchase

It was mentioned that only electric vehicles will be allowed to be operated in the new Indonesian capital in East Borneo. As we all understand, the emission of Carbon Monoxide which is resulted from fuel burning. The use of electric vehicle may reduce air pollution due to fuel burning up to 50%. The Ministry of Transport put an emphasize on research and development on this renewable source of energy, as it can reduce very large subsidy given to conventional fuel oil towards greener and more sustainable source of energy. Other advantages of using electric vehicles are its less noisy feature and its ability to be recharged relatively quickly. It is understood that home charging will take longer period than charging in charging stations. The objective of this research firstly is to understand the effect of charging period on customer decision to purchase electric vehicle. Secondly is to understand the effect of long charging period on customer decision to purchase electric vehicle. Thirdly is to understand what can be done by the government to encourage the use of electric vehicles. And lastly to understand whether electric vehicle is a durable goods.

Ecosystem-driven business opportunity identification method and web-based tool with a case study of the electric vehicle home charging energy ecosystem in Denmark

Understanding the local needs and challenges is critical for technology adoption in the energy sector. However, it is still a big challenge for most ecosystem stakeholders. Furthermore, technology adoption theories have mainly focused on the technology itself, and the business ecosystem perspective has been neglected. Therefore, this paper proposes an ecosystem-driven business opportunity identification method, a systematic approach for ecosystem stakeholders to conduct business opportunity analysis and evaluation based on the CSTEP ecosystem analysis and evaluation method. This method includes four correlated steps: Step 1: Identify the five CSTEP dimensions of the business ecosystem; Step 2: Identify potential changes in the business ecosystem; Step 3: Identify future ecosystem trends and timeline; Step 4: Select business opportunities; and Step 5: Potential solution identification. A web-based tool called opportunity identifier is developed for implementing the proposed method. A case study of the electric vehicle (EV) home charging energy ecosystem in Denmark is applied and demonstrates the application of the proposed method and the implementation of the developed web-based tool. Three value propositions are identified in the case study: (1) EV users can have optimal EV charging cost and optimal CO2 emission consumption with the intelligent EV charging algorithms that consider electricity prices, tariffs, and CO2 emission; (2) DSOs can avoid grid overloads and postpone the grid upgrade by applying intelligent EV charging algorithms; (3) Independent aggregators can aggregate EVs and participate in the ancillary service market or provide Vehicle-to-Grid services by using intelligent EV charging algorithms. Moreover, three feasible decentralized EV charging strategies (Real Time Pricing, Time-of-Use Pricing, and Timed charging) are identified as the potential solutions targeting the first value proposition.

Home charging for all: Techno-economic and life cycle assessment of multi-unit dwelling electric vehicle charging hubs

Ubiquitous electric vehicle adoption can drastically reduce greenhouse gas emissions (GHG) but will require equitable home charging infrastructure for all residences. Unlike single-family homes, Multi-Unit Dwellings (MUD) currently lack market share and access to nearby charging infrastructure partly due to expensive capital costs for reluctant residential property-owners. This work evaluates the levelized cost of charging (LCOC) for Battery Electric Vehicles (BEVs) at MUD community charging hubs through a techno-economic analysis (TEA) that leverages real-world charging data and costs. Three different MUD charging types are investigated for a baseline and optimistic case: 1.9-kW Level 1 (L1), 6.6-kW Level 2 (L2), and 50-kW Direct Current Fast Charging (DCFC) stations under three different ownership models: resident, utility, and private company. Results demonstrate L1 and L2 chargers to be less expensive than the gasoline equivalent across the United States. Further, utility and private company ownership models, which avoid initial costs for residential property owners, result in a large LCOC premium for L1 and moderate LCOC premium for L2 relative to the resident ownership model. In contrast, DCFC is shown to be expensive for baseline scenarios but economical for optimistic scenarios especially under private company ownership. This work also performs a cradle to grave (C2G) life cycle assessment (LCA) of an average passenger BEV and gasoline conventional vehicle (CV) using yearly (grid mix & vehicle parameters), hourly (grid mix), and state-level (grid mix) resolution. Results show BEVs to have lower GHG emissions (−86% to −10%) than gasoline CVs in the contiguous U.S. Next, the system boundary of the TEA is extended to the total cost of ownership (TCO) of BEVs. The TCO is then coupled with the C2G GHG emissions to calculate the cost of GHG emissions reduction. Ultimately, the cost of GHG emissions reduction from MUD BEVs relative to gasoline CVs is shown to be negative for every scenario except baseline DCFC, meaning MUD BEV charging infrastructure can be a cost-effective endeavor to reduce GHG emissions.

Where should electric vehicle users without home charging charge their vehicle?

• Curbside charging stations are still highly costly compared to other options. • The need for curbside charging is often overestimated in literature. • Charging possibilities at workplace and shopping facilities should be incentivized. An often-heard argument against using plug-in electric vehicles (PEV) by urban dwellers is the missing curbside charging option. Some users are even expecting these charging stations to deliver cheap electricity. However, from an economic perspective several arguments speak against this hope and, furthermore, the need of curbside chargers is often exaggerated in literature. Consequently, we shed more light into these two hypotheses (H1. curbside charging is very costly and H2. there is hardly any need for curbside charging) and base our arguments on current and representative mobility data from Germany. Policymakers may focus stronger on charging offers at workplace or shopping facilities for achieving an efficient allocation of charging infrastructure.

An Edge-Supported Blockchain-Based Secure Authentication Method and a Cryptocurrency-Based Billing System for P2P Charging of Electric Vehicles.

The popularity of electric vehicles (EVs) is constantly increasing, as they use relatively greener, sustainable energy. However, it is a fact that the charging stations for EVs are yet to meet the demand. It could be a great solution if a peer-to-peer (P2P) charging system could be initiated by anyone who wants to make their garage's charge points publicly available for commercial purposes, named a home charging station (HCS). In this work, our idea is to bring interested charging stations under a network of nodes and a blockchain-based management system, where the blockchain is responsible for ensuring the authenticity of both the charging stations and charge receiver. A cryptocurrency-based payment system has also been proposed to ensure transactions' security, integrity, transparency, and immutability. A reputation management system is applied to maintain the quality of service. Miners with high processing power are used to alleviate lagging during block creation, supported by edge servers. The proposed system has been implemented by using virtual machines. A theoretical analysis is presented to assess the compatibility and possible cost requirements to implement the system in a real-world scenario.

Real-world charging behavior and preferences of electric vehicles users in Germany

As energy consumption and greenhouse gas emissions in the transport sector have increased continuously in recent years, electric vehicles have become a potential solution to achieve environmental goals in this sector. The uptake of electric vehicle is strongly dependent on sufficient charging infrastructure. While much research has been conducted on electric vehicle charging simulations and projections, there is a research gap on real-world charging by actual users. Therefore, we conducted a survey on charging behavior and preferences in Germany in 2020 with around 4,000 electric vehicle users. The survey included a stated choice experiment and a willingness-to-pay-analysis. We found that participants’ charging behavior is dominated by home charging and that public infrastructure is perceived to be insufficient. Next to charging prices, measures of comfort through the occupancy rate of charging infrastructure and additional waiting time are driving factors when making the decision to charge. Participants specified an acceptable time for additional walking distances when parking at charging facilities between 5 and 10 minutes. High abstention rates in answering some questions indicate the need for sufficient education strategies considering existing and new charging technologies. Drivers with high annual mileage and battery electric vehicle users are willing to pay more for additional charging power. Users are open to smart charging, as long as flexibility for spontaneous trips is maintained. This research offers timely insights into real-world charging behavior and preferences, while providing recommendations for the future roll out of charging infrastructure in Germany.

Benefits of an Electric Road System for Battery Electric Vehicles

Electric road systems (ERS)—infrastructure that allows for charging while driving—are currently considered in Sweden for electrifying long-haul trucking. The technology can also charge battery electric passenger vehicles (BEVs). This study utilizes real-world car movement data in Sweden and detailed spatial analysis to explore to what extent ERS could displace stationary charging if it is available for BEVs and the expected benefits. We find that ERS utilization and the minimum battery ranges depend more on visited locations and home locations and less on the annual travel distances of car users. The median battery ranges required by rural residents are 15–18% greater than for urban residents. Our scenarios suggest that a mix of ERS and home-charging would achieve the most significant benefits. ERS with home charging reduces the required battery range by 62–71% in the main scenarios, and the net savings from smaller BEV batteries exceed the cost of ERS. Eliminating all stationary charging is feasible for many but not all vehicles. Utilizing ERS could also significantly reduce peak BEV charging by distributing charging throughout the day. We also find that there is a considerable difference between the maximum possible and minimum needed charging on ERS, which can significantly influence ERS revenues. Future studies can expand to include other modes (e.g., trucks) to provide more holistic assessments of economic benefits and charging needs.

Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption

Electric vehicles will contribute to emissions reductions in the United States, but their charging may challenge electricity grid operations. We present a data-driven, realistic model of charging demand that captures the diverse charging behaviours of future adopters in the US Western Interconnection. We study charging control and infrastructure build-out as critical factors shaping charging load and evaluate grid impact under rapid electric vehicle adoption with a detailed economic dispatch model of 2035 generation. We find that peak net electricity demand increases by up to 25% with forecast adoption and by 50% in a stress test with full electrification. Locally optimized controls and high home charging can strain the grid. Shifting instead to uncontrolled, daytime charging can reduce storage requirements, excess non-fossil fuel generation, ramping and emissions. Our results urge policymakers to reflect generation-level impacts in utility rates and deploy charging infrastructure that promotes a shift from home to daytime charging.

Mobile charging stations for EV charging management in urban areas: A case study in Chattanooga

The advancement of fixed charging stations (FCS) has facilitated electric vehicle (EV) charging and increased EV adoption. FCSs are especially important in dense urban areas, where home charging is not an option. However, FCSs’ construction is limited by budget, fragile power grid infrastructure, and site constraints, among others. Therefore, suitable locations for building FCSs are limited. Even in the presence of FCSs, EV drivers face challenges such as long charging times and inconvenient charging locations. Mobile charging stations (MCS), which allow for scheduling and convenient charging, can be a supplementary charging technology to address these shortcomings and allow rapid expansion of charging infrastructure, assuming the MCS can be scheduled efficiently. This paper develops an optimization framework for the optimal charging management of EVs considering a multi-charger system integrating different types of FCSs and MCSs. Considering the EV driver’s travel trajectory and time value, the proposed framework finds the optimal charging technology and location to minimize the EV user’s overall charging cost and time. The model is implemented in Chattanooga, TN, USA, where the evaluation results demonstrated that MCSs are the optimal charging method for many EV users. Moreover, the results indicated that MCS mitigates the power grid stress caused by EV charging during peak hours.