Sustainable integration of wind and grid resources for electric vehicles charging in low wind speed region: A techno-economic assessment

- The growing adoption of electric vehicles (EVs) worldwide has brought new challenges in the realm of power management and grid stability. One of the key components in this ecosystem is the EV charger, a device that facilitates energy transfer between the power grid and the EV battery. The increasing adoption of electric vehicles (EVs) necessitates the development of advanced charging systems that are both efficient and compatible withmodern electrical grids. This paper presents the design and implementation of a high efficiency EV charger based on a Single-Ended Primary-Inductor Converter (SEPIC) topology integrated with Power Factor Correction (PFC). The SEPIC converter is chosen for its ability to operate effectively across a wide range of input and output voltages, making it ideal for the dynamic requirements of EV charging. The SEPIC converter is selected for its ability to efficiently manage varying input voltages and provide a stable output, making it ideal for EV charging applications. The SEPIC topology offers the flexibility to both step up and step down the input voltage, ensuring consistent charging regardless of fluctuations in the grid or renewable energy sources. This capability is crucial for maintaining the health and longevity of the EV battery. Through this project we are going to simulate the entire working of the proposed EV charger using MATLAB SIMULINK and also to view the operation of this EV charger. Key Words: EV Charger, SEPIC Converter, SoC, PFC.

This paper presents a comprehensive model for electric vehicle chargers (EVC) focused on scheduling loads in electric vehicle charging stations (EVCS). It also applies practical information from data gathered by Open Charge Point Protocol (OCPP) for validation of results. The scheduling strategy applies an evolutionary particle swarm optimization (EPSO) metaheuristic to set the hours for charge of the EV. The battery charging model combines the Kinetic Battery Model (KiBaM) and a Voltage Model (VM). A practical validation for the battery model accuracy is made with real data gathered by OCPP. The results showed a good operation for the framework in the EVCS in terms of economic cost and grid impact.. The results also showed a good performance for the battery model. Finally, the OCPP confirmed the results of the model with low errors in terms of performance.

Efficient unit commitment strategy in a modern workplace facilitated with electric vehicle (EV) chargers and energy storage systems requires implementation of optimal battery cycling for both local storage system and electric vehicle batteries. In order to achieve this goal, it is necessary to address the battery health in the energy management strategies of commercial buildings. A fair battery cycling approach that could consider the interests of both parties in a workplace (including the system operator and the EV owners) requires access to detailed information on battery performance and degradation‐associated costs. In this study, a detailed investigation is carried out on the optimal battery cycling in a workplace that is facilitated with an EV charging station, energy storage system and renewable energy generation. This is carried out by employment of a tailored unit commitment model that can address the battery health for EVs, individually. This study illustrates how a business owner and the employees that own electric vehicles can benefit from bidirectional battery cycling in an equitable way without compromising their financial interests in the energy market.

Chapter 15 - Demonstration of EV chargers on real testbed and its impact on the grid

The high-power rectifiers in electric vehicle (EV) charging stations may bring serious harmonic pollution to power grid. For different types of EV charging stations, one of the issues concerned in the engineering is that how much capacity of the active power filter (APF) and reactive power compensator should be configured. Previous research has given preliminary configuration principle and calculation formula of the APF's capacity. On this basis, based on the configuration parameters of typical EV chargers and charging stations, firstly, this paper gets the maximum harmonic current and power factor values in the output voltage range of the different EV chargers by doing lots of simulations. Secondly, the capacity of APF and reactive power compensator needed for single EV charger is calculated. Thirdly, the mathematical formula of APF's configuration capacity for the whole EV charging station is presented. Finally, the configuration capacity's calculation results of APF and reactive power compensator for different EV charging stations are given.

The increasing penetration of Electric Vehicles (EVs) presents significant challenges in integrating EV chargers. To address this, precise smart EV charging strategies are imperative to prevent a surge in peak power demand and ensure seamless charger integration. In this article, a smart EV charging pool algorithm employing optimal control is proposed. The main objective is to minimize the charge point operator’s cost while maximizing its EV chargers’ flexibility. The algorithm adeptly manages the charger pilot signal standard and accommodates the non-ideal behavior of EV batteries across various vehicle types. It ensures the fulfillment of vehicle owners’ preferences regarding the departure state of charge. Additionally, we develop a data-driven characterization of EV workplace chargers, considering power levels and estimated battery capacities. A novel methodology for computing the EV battery’s arrival state of charge is also introduced. The efficacy of the EV charging algorithm is evaluated through multiple simulation campaigns, ranging from individual charger responses to comprehensive charging pool analyses. Simulation results are compared with those of a typical minimum-time strategy, revealing cost reductions and significant power savings based on the flexibility of EV chargers. This novel algorithm emerges as a valuable tool for accurately managing the power demanded by an EV charging station, offering flexible services to the electrical grid.

With the proliferation of vehicular mobility traces because of inexpensive on-board sensors and smartphones, utilizing them to further understand road movements have become easily accessible. These huge numbers of vehicular traces can be utilized to determine where to enhance road infrastructures such as the deployment of electric vehicle (EV) charging stations. As more EVs are plying today’s roads, the driving anxiety is minimized with the presence of sufficient charging stations. By correctly extracting the various transportation parameters from a given dataset, one can design an adequate and adaptive EV charging network that can provide comfort and convenience for the movement of people and goods from one point to another. In this study, we determined the possible EV charging station locations based on an urban city’s vehicular capacity distribution obtained from taxi and ride-hailing mobility GPS traces. To achieve this, we first transformed the dynamic vehicular environment based on vehicular capacity into its equivalent urban single snapshot. We then obtained the various traffic zone distributions by initially utilizing k-means clustering to allow flexibility in the total number of wanted traffic zones in each dataset. In each traffic zone, iterative clustering techniques employing Density-based Spatial Clustering of Applications with Noise (DBSCAN) or clustering by fast search and find of density peaks (CFS) revealed various area separation where EV chargers were needed. Finally, to find the exact location of the EV charging station, we last ran k-means to locate centroids, depending on the constraint on how many EV chargers were needed. Extensive simulations revealed the strengths and weaknesses of the clustering methods when applied to our datasets. We utilized the silhouette and Calinski–Harabasz indices to measure the validity of cluster formations. We also measured the inter-station distances to understand the closeness of the locations of EV chargers. Our study shows how CFS + k-means clustering techniques are able to pinpoint EV charger locations. However, when utilizing DBSCAN initially, the results did not present any notable outcome.

A fully decentralized controlled (FDC) electric vehicle (EV) charger, where its design is intended to mitigate the charging impact on power grids, is proposed in this paper. The proposed FDC EV charger uses the parameters measured from the power grid, EV charger and EV battery pack to adjust the charging current. Fuzzy logic control is used in this paper to integrate these measured parameters into the proposed FDC EV charger. As the proposed charger can be realized without a centralized control center and information exchanges between EV chargers, an FDC scheme for EV charger can therefore be effectively achieved. A prototype of the proposed FDC EV charger with a rated power of 500 W is implemented. Experimental results verify that the proposed charger can automatically adjust the charging current according to variations in the power grid and EV. Simulations analyze the impact of 100 EVs with a rated power of 7 kW charged simultaneously. Simulation results show that the EV charging impact on power grids can be effectively mitigated by the proposed FDC EV chargers.

Demonstration of denial of charging attack on electric vehicle charging infrastructure and its consequences

An Electric Vehicle (EV) charger or Electric Vehicle Supply Equipment (EVSE) is a piece of equipment that supplies electrical power for charging plug–in electric vehicles. Although batteries can only be charged with Direct Current (DC) power, most electric vehicles have an onboard Alternative Current AC—to—DC converter and most fully electric cars can accept both AC and DC power. The adoption of EVs can bring about significant relief in noise pollution and also environmental pollution if the required electricity is generated using renewable sources. DC charging stations of various levels are commonly equipped with multiple ports of various levels to be able to charge a wide variety of EVs. EVSEs are found at various facilities such as street–side or retail shopping centers, government facilities, and other parking areas. To ensure a sustainable environment by reducing the carbon emissions from vehicles, the use of EVs needs to be promoted. The need for having Electric Vehicle Charging Stations (EVCS) in any region depends upon the demand and cluster density of EVs in that region and is a major factor in the process of promoting the use of EVs and facilitating sustainable tourism using cleaner fuels. The authors of this study have located the various types and numbers of EVSEs throughout all the states and union territories of India, showing the emerging use of EVs so that EV users can conveniently locate charging stations and plan their routes accordingly. Furthermore, other citizens may be encouraged to own and use EVs for better environmental sustainability.

This paper presents a bridgeless totem pole boost converter (BLTPBC) fed synchronous full bridge inductor-inductor-capacitor (FBLLC) converter based electric vehicle (EV) charger as a fundamental building block for larger capacity EV infrastructure. This EV charger comprises of BLTPBC as a front-end power factor correction (PFC) converter followed by a high efficiency synchronous FBLLC converter for DC-DC conversion. The PFC TPBLB is operated in continuous inductor conduction mode at fixed frequency, while the control of synchronous FBLLC converter is performed using pulse frequency modulation (PFM). The performance of this EV charger is deeply analysed during steady state and transient conditions by a developed proto-type and are discussed and presented. The performance of this EV charger in a large EV structure composed by paralleling these chargers is also presented by virtue of its short circuit performance.

This paper presents simple equivalent models of electric vehicle (EV) chargers, based on the measurements of a range of actual EVs. The developed models of the EV chargers are capable of correctly reproducing instantaneous input current waveforms, retaining all relevant electrical characteristics, including harmonic content. To analyse the effects of increased penetrations EV chargers on low-voltage network, the developed EV charger models are combined with the models of existing loads, as a part of the aggregate residential load mix.

Electric vehicle (EV) ownership is skyrocketing while authorities are scrambling to expand their charging infrastructure networks. In urban areas, they all face the ever-pertinent question of maximizing the marginal benefits of each new EV charger. This paper aims to make the case of coupling EV charging stations with micro mobility-hubs as a way of increasing each station’s area of influence, thus amplifying its potential service population. The case study of the Municipality of Kifissia is used to demonstrate the benefits of an EV charging station coupling with micro-mobility. The model will take into account the potential EV users of the selected area, available and planned EV charging stations and the local road network characteristics in order to formulate an alternative way of combined micro-mobility and EV infrastructure planning. The model is then tested in existing urban environments and with emerging results indicating that the theory can be a valuable tool in charging infrastructure planning. The developed methodology led to the delineation of the influence area of EV chargers with or without micro-mobility and the determination of the most suitable ones for coupling. Thus, it paves the way for a novel less-is-more approach to incentivizing EV usage and planning the necessary infrastructure – one of particular importance to national and local authorities that are just now embracing e-mobility.

Mapping tools can play an important role in incorporating equity into planning, implementing, and evaluating investments in electric vehicle (EV) charging stations, also referred to as EV chargers or electric vehicle supply equipment (EVSE). Federal, state, and local organizations need methodologies for using mapping tools as they pursue equity-focused goals to ensure that the benefits of investments in EV chargers flow to energy and environmental justice (EEJ) underserved communities. This report provides examples of how to apply mapping tools to identify priority locations for installing EV chargers that may benefit EEJ underserved communities through four EV charger planning approaches: corridor charging, community charging, fleet electrification, and diversity in STEM and workforce development. It also explores various methodologies for calculating low-public EVSE density. Ensuring that the benefits of EV charger investments flow to underserved communities involves prioritizing locally identified needs and incorporating community input when choosing charging station locations. Installing EV chargers in a census tract identified as an EEJ underserved community does not inherently mean that those EV chargers provide benefits to residents of that community. In addition, representatives of historically disadvantaged communities or environmental justice communities have concerns that installing EV chargers in their communities could potentially exacerbate or propagate existing inequities. While the methodologies described in this report may help identify priority census tracts for equity-focused EV charger investment, additional community engagement and site evaluation are necessary to determine whether EV chargers are accessible, affordable, and convenient to EEJ underserved community residents and what benefits the local community is looking to realize with EV charger installations. This report is the culmination of many discussions with project leaders from DOE-funded projects deploying EV chargers in communities across the nation, organizations representing EEJ underserved communities, state agencies developing EV investment plans, utilities making major EV investments, and DOE national laboratory experts working in transportation electrification. The authors distributed a draft report for peer review, and reviewer comments are summarized in this report. These methodologies are likely to evolve as more EV charger funding programs are implemented and more real-world data is available to measure the effectiveness of strategies for incorporating equity in EV charger deployment projects. Continued efforts to document best practices and critically evaluate whether equity-focused programs achieve their goals are needed as transportation electrification proceeds at the local, regional, and national levels.

In order to pursuit a more eco-friendly lifestyle, many changes are being done to our daily life. One of these changes is the adoption of electric vehicles (EVs). These zero emission and electricity driven vehicles have been proved to be effective in reducing roadside air pollution and green house gas emission. Not only are they able to assist in pollution reduction, EVs can also utilize renewable energy resources, making them much greener than conventional gasoline vehicles. The Hong Kong government has been promoting the adoption of EVs since 2010. They have been providing different kinds of incentives, such as tax exemptions and subsidies to companies for conducting EV trails. The government want to attract more people or companies to adopt EVs. Despite efforts of the government, EV is yet to be a significant kind of vehicle in Hong Kong. In my dissertation, I suggested a new way of promotion for EV adoption: integration of smart grid technology and EVs. The current smart grid technology development in Hong Kong is at a very primitive stage, there is a lot of space for improvement. For my study, I had conducted an opinion survey on people’s perception of both EV adoption and the introduction of smart grid. The survey results showed the top three reasons for people not to buy EVs are high price, insufficient range & battery capacity, and insufficient EV chargers. More importantly, the survey showed the willingness to purchase EVs increased from 23% at the current situation to 56% with smart grid being applied widely. From this result, I concluded that the use of smart grid technology would increase people’s willingness to purchase EV. Based on these results, I have suggested the government and electricity companies should focus future EV promotion in the following areas: solution to range anxiety of people, smart grid technology in Hong Kong, dynamic electricity tariff system, integration of renewable energy into generation fuel mix and development on V2G application. At the end of my paper, I have given out some possible ways of improvement for the government to better its EV promotion policies in the future. The suggested improvements are focused on specific subsidy schemes for EV upgrades, regulations for EV charger use and construction, and development of a steering committee for smart grid adoption. Possible topics for future studies base on this paper are also suggested in the ending chapter.