Impacts of COVID-19 on Electric Vehicle Charging Behavior: Data Analytics, Visualization, and Clustering

COVID-19 pandemic has infected millions and led to a catastrophic loss of lives globally. It has also significantly disrupted the movement of people, businesses, and industries. Additionally, electric vehicle (EV) users have faced challenges in charging their vehicles in public charging locations where there is a risk of COVID-19 exposure. However, a case study of EV charging behavior and its impacts during the SARS-CoV-2 is not addressed in the existing literature. This paper investigates the impacts of COVID-19 on EV charging behavior by analyzing the charging activity during the pandemic using a dataset from a public charging facility in the USA. Data visualization of charging behavior alongside significant timelines of the pandemic was utilized for analysis. Moreover, a cluster analysis using k-means, hierarchical clustering, and Gaussian mixture models was performed to identify common groups of charging behavior based on the vehicle arrival and departure times. Although the number of vehicles using the charging station was reduced significantly due to lockdown restrictions, the charging activity started to pick up again since May 2021 due to an increase in vaccination and easing of public restrictions. However, the charging activity currently still remains around half of the activity pre-pandemic. A noticeable decline in charging session length and an increase in energy consumption can be observed as well. Clustering algorithms identified three groups of charging behavior during the pandemic and their analysis and performance comparison using internal validation measures were also presented.

Tertiary Control for Energy Management of EV Charging Station Integrated With PV and Energy Storage

Along with the rapid increase in the number of electric vehicles, more and more EV charging stations tend to have charging infrastructure, rooftop photovoltaic and energy storage all together for energy saving and emission reduction. Compared with individual design for each of the components in such kind of systems, an integrated design can result in higher efficiency, increased reliability, and lower total capital cost. This paper mainly focuses on the tertiary control strategy for dynamic state operation, such as PV generation fluctuation and random arrival/leave of EVs. The tertiary control aims to achieve stable operation under dynamic states, as well as to optimize the energy flow in the station to realize maximal operational benefits with constraints such as peak/valley price of electricity, state of discharge limitation of battery, etc. In this paper, four energy management functions in tertiary control level are proposed, and their performance is verified by simulations. By using prediction of PV power and EV load in the following 72 h, a novel tertiary control logic is proposed to optimize PVC and ESC power flow by changing their droop characteristics, so that minimum operational cost for the station can be achieved. Furthermore, a sensitivity analysis is conducted for three parameters, including ES battery capacity, weather influence, and PV and EV load prediction error. The results from sensitivity analysis indicate that ES battery capacity and weather condition lead to a great impact on the operational cost of the integrated charging station, while a typical prediction error of PV power and EV load will not influence the optimization result significantly.

Charging Station Planning for Electric Vehicles

Charging station (CS) planning for electric vehicles (EVs) for a region has become an important concern for urban planners and the public alike to improve the adoption of EVs. Two major problems comprising this research area are: (i) the EV charging station placement (EVCSP) problem, and (ii) the CS need estimation problem for a region. In this work, different explainable solutions based on machine learning (ML) and simulation were investigated by incorporating quantitative and qualitative metrics. The solutions were compared with traditional approaches using a real CS area of Austin and a greenfield area of Bengaluru. For EVCSP, a different class of clustering solutions, i.e., mean-based, density-based, spectrum- or eigenvalues-based, and Gaussian distribution were evaluated. Different perspectives, such as the urban planner perspective, i.e., the clustering efficiency, and the EV owner perspective, i.e., an acceptable distance to the nearest CS, were considered. For the CS need estimation, ML solutions based on quadratic regression and simulations were evaluated. Using our CS planning methods urban planners can make better CS placement decisions and can estimate CS needs for the present and the future.

Drivers of EV Charging Infrastructure Entrepreneurship in India

The existing research advocating entrepreneurship as an important way to increase the uptake of electric vehicles (EVs) in developing countries and EV charging business is also playing a crucial role in increasing the adoption of EVs. EV charging is important for EV adoption, and entrepreneurship is also important for EV adoption; therefore, it is important that we must understand what mobilizes or prevents EV charging entrepreneurship. This chapter aimed at explaining drivers of EV charging entrepreneurship. A survey of 121 potential entrepreneurs shows that personal attitude, self-confidence, and opportunity perceptions shape the decision to engage in EV charging entrepreneurship. Policy measures to boost EV charging entrepreneurship have been suggested.

A Comprehensive Review of Blockchain Technology Implementation in the EV Charging Infrastructure

Charging infrastructure is a key factor in successful electric vehicle adoption. Charging stations are still a fragmented market in terms of ownership, lack of standards, and charging protocols. The increasing decentralised grid has made energy and communication flow bi-directional. Challenges arise in maintaining the increasing decentralised structure, security, and privacy of the network. Blockchain facilitates the interconnectedness of such a distributed and decentralised network. Blockchain's versatility lies in its transparent and immutable decentralized architecture that enables direct transactions between users without the need of a middleman. It provides powerful safeguards against cyberattacks with its advanced cryptography enabling privacy-preserving authentication. This chapter presents a comprehensive review on the application of blockchain technology in EV charging infrastructure such as facilitating the peer-to-peer energy exchange, increased security and privacy, immutable transactions, and mitigating trust issues among the participants in the charging infrastructure.

Impact of Charging on Battery Life and Battery Degradation in Electric Vehicles

Electrical vehicles are the future of the world; hence, there is a necessity to pave the way for the upcoming technology and to ensure its contribution to the society fairly. Nevertheless, if the EVs completely replaced the fuel-based cars, more EV charging stations would be needed which might develop overconsumption of the main grid power causing remarkable instability. Consequently, the micro grids become the solution to this problem, in which they are defined as relatively small networks of energy sources and loads at the distribution level that aim to provide electricity to remote locations where the charging stations are located. In this chapter, the EV is considered as a load to the micro grid indirectly through the EV charging stations. Thus, micro grid loads will be retrieved from experimental data of an actual prototype electric vehicle to reflect on the battery degradation in a micro-grid connected system.

Battery Swapping Station

State-of-the-art research to solve the grid congestion due to EVs is focused on smart charging and using (centralized, de-centralized, vehicle-to-grid) stationery energy storage as a buffer between times of peak and off-peak demand. On the other hand, the charging of EVs introduces new challenges and opportunities. This can prove to be beneficial for the EV aggregator as well as to consumers, regarding the economy. Also, EV as distributed storage makes the grid more steady, secure, and resilient by regulating frequency and the spinning reserve as backup power. However, the charging time and range anxiety lead to peak challenges for the use of EVs. In this chapter battery swapping station (BSS) as solution to the EV charging station is discussed.

Proposed Power Systems Planning in Indian Scenario for Integrating EV Charging Infrastructure

The growing concern about fossil energy exhaustion, air pollution, and ecological deprivation has made electric vehicles (EVs) a practical option in contrast to combustion engine-driven vehicles. In any case, driving extent uneasiness is one of the innate inadequacies related with EVs. Massive integration of EV charging load into the power system may be a threat to the distribution network. Spontaneous situation of charging stations in the distribution system and uncoordinated charging will augment the load demand thereby resulting in voltage instability, deterioration of reliability indices, harmonic distortions, and escalated power losses. This chapter will concentrate on breaking down the effect of EV chargers on the working parameters, for example, voltage dependability, unwavering quality, and force misfortune. The examination will be completed on standard test systems. The discoveries of the proposed part will evaluate the effect of EV charging load on the working parameters of the distribution system and help in proposing a framework for charging station planning.