Electric Vehicle Supply Equipment Research Articles

Cybersecurity Certification Requirements for Distributed Energy Resources: A Survey of SunSpec Alliance Standards

This survey paper explores the cybersecurity certification requirements defined by the SunSpec Alliance for Distributed Energy Resource (DER) devices, focusing on aspects such as software updates, device communications, authentication mechanisms, device security, logging, and test procedures. The SunSpec cybersecurity standards mandate support for remote and automated software updates, secure communication protocols, stringent authentication practices, and robust logging mechanisms to ensure operational integrity. Furthermore, the paper discusses the implementation of the SAE J3072 standard using the IEEE 2030.5 protocol, emphasizing the secure interactions between electric vehicle supply equipment (EVSE) and plug-in electric vehicles (PEVs) for functionalities like vehicle-to-grid (V2G) capabilities. This research also examines the SunSpec Modbus standard, which enhances the interoperability among DER system components, facilitating compliance with grid interconnection standards. This paper also analyzes the existing SunSpec Device Information Models, which standardize data exchange formats for DER systems across communication interfaces. Finally, this paper concludes with a detailed discussion of the energy storage cybersecurity specification and the blockchain cybersecurity requirements as proposed by SunSpec Alliance.

Efficient energy management and cost optimization using multi-objective grey wolf optimization for EV charging/discharging in microgrid

The depletion of conventional energy sources coupled with the rising demand for electric vehicles (EVs) has significantly underscored the necessity for electric vehicle supply equipment (EVSE) with advanced energy supply management within microgrids. Effective energy management of EVs and EVSEs is imperative to satisfy EV owners and stabilize microgrids. This paper introduces multi-objective grey wolf optimization (MOGWO) to optimize EVSE and EV charging costs. MOGWO achieves substantial cost savings through dynamic pricing based on time of day, state-of-charge and hour-based scheduling which promotes off-peak charging thereby enhancing system efficiency and reducing costs. The algorithm also provides flexibility for trip interruptions and outperforms other optimization algorithms in minimizing EV charging/discharging costs by achieving reductions of up to ₹488 and obtaining average grid efficiency up to 76.41 % during charging and 87.41 % during discharging. Integrating Vehicle-to-Grid and Grid-to-Vehicle systems enhances microgrid resilience and delivers economic benefits to EV owners. The cost optimization for EV charging/discharging has been executed using MATLAB 2023a software to determine the most cost-effective charging paths by considering energy availability and grid conditions. The evolving sustainable energy landscape combined with MOGWO paves the way for smarter and more resilient microgrids in the era of electrified transportation.

Development of a Cost-Driven, Real-Time Management Strategy for e-Mobility Hubs Including Islanded Operation

The installation of electric vehicle supply equipment (EVSE) increases demand and peak loads, potentially straining existing energy distribution infrastructure. Dispersed and inadequately planned placement of charging points (CPs) can disrupt the electrical grid, surpass contracted demand thresholds, and require infrastructure upgrades, thereby incurring unfeasible costs for Distribution System Operators (DSOs). In this context, it is necessary to recognize the role of business models in enabling effective electrification of the transportation sector. In response to these challenges, this paper introduces a novel e-mobility hub management strategy, tailored for implementation in the Brazilian context. The proposed strategy revolves around a microgrid configuration encompassing dispatchable and photovoltaic generation, a battery energy storage system (BESS), EVSE infrastructure, and local loads. Moreover, this centralized controller facilitates the implementation of dynamic pricing and demand-response mechanisms, integral to business models seeking to integrate EVSE into the distribution grid. To validate the efficacy of the proposed solution, hardware-in-the-loop (HIL) simulations of the microgrid system are conducted. These simulations, incorporating the centralized controller, serve as a tool for assessing system performance and viability before on-site equipment deployment. Finally, this paper concludes with the insights gleaned from test analysis and its discussion through a selection of the most expressive scenarios, including islanded and connected operation modes.

Electric vehicle supply equipment monitoring and early fault detection through autoencoders

This paper presents a novel approach to detecting anomalies in Electric Vehicle charging unit power profiles using a combination of Autoencoders with LSTM techniques. This study presents a robust methodology, combining the two Machine Learning techniques, for early fault estimation in a real-world case study. The proposed methodology offers significant advantages over existing methods by providing a more comprehensive analysis of anomalous trends. To validate the effectiveness of the proposed methodology, the authors tested it on real Electric Vehicles charging power curves provided by an Italian Distribution System Operator recorded on a historical database and compared the performances with the ones of a traditional anomaly detection technique. The results of the study, tested on Electric Vehicles Supply Equipment or charging stations, demonstrate that the proposed approach is highly effective in detecting anomalous trends in Electric Vehicles charging profiles.

SoC Profile Reconstruction in Residential EV Charging: Assessing the Degradation of V1G and V2G in Denmark

The development of Smart Charging (SC) strategies for Electric Vehicles (EVs) is on the rise, driven by the potential benefits for both customers and grid operators. While several studies have explored the impact of these strategies on battery degradation, there is a lack of studies based on real-world data. To overcome the limited information provided by the current EV-EVSE (EV Supply Equipment) communication protocols, a methodology to reconstruct State of Charge (SoC) profiles based on the charging power is proposed and used to reconstruct the profiles and analyse the battery degradation for three residential EVSEs in Denmark, comparing degradation trends in under Uncontrolled Charging (UC) mode, with the SC ones. Results show that the economic profits from unidirectional (V1G) SC strategies based on price, offer significant cost savings (10-22% annually) and reduce calendar ageing by up to 4% over a decade. V2G strategies entail modest increases in cost savings at the cost of a minimal additional degradation.

Experimental Investigation of a Distributed Architecture for EV Chargers Performing Frequency Control

The demand for electric vehicle supply equipment (EVSE) is increasing because of the rapid shift toward electric transport. Introducing EVSE on a large scale into the power grid can increase power demand volatility, negatively affecting frequency stability. A viable solution to this challenge is the development of smart charging technologies capable of performing frequency regulation. This paper presents an experimental proof of concept for a new frequency regulation method for EVSE utilizing a distributed control architecture. The architecture dynamically adjusts the contribution of electric vehicles (EVs) to frequency regulation response based on the charging urgency assigned by the EV users. The method is demonstrated with two Renault ZOEs responding to frequency fluctuation with a combined power range of 6 kW in the frequency range of 50.1 to 49.9 Hz. The results confirm consistent power sharing and effective frequency regulation, with the system controlling the engagement of the EVs in frequency regulation based on priority. The delay and accuracy analyses reveal a fast and accurate response, with the cross-correlation indicating an 8.48 s delay and an average undershoot of 0.17 kW. In the conclusions, the paper discusses prospective improvements and outlines future research directions for integrating EVs as service providers.

Electric Vehicle Supply Equipment Day-Ahead Power Forecast Based on Deep Learning and the Attention Mechanism

Electric Vehicle Supply Equipment Day-Ahead Power Forecast Based on Deep Learning and the Attention Mechanism

Fault analysis for DC Bus-integrated energy storage system, electric vehicle supply equipment, and photo voltaic systems

Reliable access to cost-effective electricity is the backbone of the U.S. economy, and energy storage is an integral element of the power system with high penetration of Distributed energy resources (DERs). Investment in energy storage is essential for keeping pace with the increasing demands for electricity arising from continued growth in U.S. productivity, continued expansion of national cultural imperatives (e.g., emergence of the distributed grid and electric vehicles), and the projected increase in DERs. This research is on the forefront of this transition with fault analysis execute for a real system to be implemented in New York City at a Utility substation. The project seeks to pair a grid-connected battery energy storage system (BESS), solar photovoltaic (PV) system, and an electric vehicle charging system (EVCS) on a common DC bus. A transient model has been developed and different fault scenarios (i.e., high-impedance and low-impedance faults) have been simulated, at various points of the system for several durations. The objective of this study is to determine the requirements for electrical protection equipment, i.e., DC Circuit Breakers (DCCBs) in terms of capacity and fault clearing time that can ensure stable operation of the DC bus system while meeting the utility and IEEE requirements for system stability. The results showed that fast-response DCCBs is a key element for the system. Solid-State DC breakers with ultra-high speed must be deployed for prompt detection/isolation of faults. Actual ratings of converters and allied equipment need to be considered before the finalization of ratings and specification of protection equipment.

Index Air Quality Monitoring for Light and Active Mobility.

Light and active mobility, as well as multimodal mobility, could significantly contribute to decarbonization. Air quality is a key parameter to monitor the environment in terms of health and leisure benefits. In a possible scenario, wearables and recharge stations could supply information about a distributed monitoring system of air quality. The availability of low-power, smart, low-cost, compact embedded systems, such as Arduino Nicla Sense ME, based on BME688 by Bosch, Reutlingen, Germany, and powered by suitable software tools, can provide the hardware to be easily integrated into wearables as well as in solar-powered EVSE (Electric Vehicle Supply Equipment) for scooters and e-bikes. In this way, each e-vehicle, bike, or EVSE can contribute to a distributed monitoring network providing real-time information about micro-climate and pollution. This work experimentally investigates the capability of the BME688 environmental sensor to provide useful and detailed information about air quality. Initial experimental results from measurements in non-controlled and controlled environments show that BME688 is suited to detect the human-perceived air quality. CO2 readout can also be significant for other gas (e.g., CO), while IAQ (Index for Air Quality, from 0 to 500) is heavily affected by relative humidity, and its significance below 250 is quite low for an outdoor uncontrolled environment.

Electric vehicle supply equipment location and capacity allocation for fixed-route networks

Electric vehicle (EV) supply equipment location and allocation (EVSELCA) problems for freight vehicles are becoming more important because of the trending electrification shift. Some previous works address EV charger location and vehicle routing problems simultaneously by generating vehicle routes from scratch. Although such routes can be efficient, introducing new routes may violate practical constraints, such as drive schedules, and satisfying electrification requirements can require dramatically altering existing routes. To address the challenges in the prevailing adoption scheme, we approach the problem from a fixed-route perspective. We develop a mixed-integer linear program, a clustering approach, and a metaheuristic solution method using a genetic algorithm (GA) to solve the EVSELCA problem. The clustering approach simplifies the problem by grouping customers into clusters, while the GA generates solutions that are shown to be nearly optimal for small problem cases. A case study examines how charger costs, energy costs, the value of time (VOT), and battery capacity impact the cost of the EVSELCA. Charger equipment costs were found to be the most significant component in the objective function, leading to a substantial reduction in cost when decreased. VOT costs exhibited a significant decrease with rising energy costs. An increase in VOT resulted in a notable rise in the number of fast chargers. Longer EV ranges decrease total costs up to a certain point, beyond which the decrease in total costs is negligible.

Analyzing the urban-rural divide: Understanding geographic variations in charging behavior for a user-centered EVSE infrastructure

Understanding charging behavior in relation to its geographic locale is crucial for fostering a user-centered and equitable electric vehicle supply equipment (EVSE) infrastructure. This study employs a comprehensive and multivariate approach to investigate the utilization of public Level 2 electric vehicle chargers, revealing notable differences in charging behavior across provinces and varying urbanity levels in Canada. The findings showcase a clear urban-rural divide in charging behavior, characterized by distinct patterns across different provinces. While a weekly repetitive charging demand pattern is evident, high-demand periods diverge among charging networks. Furthermore, the study identifies charging demand trends within these networks, which display variations in direction and shape. The results of this study indicate that charging behavior is inconsistent between different charging networks, indicating that stakeholders should recognize the necessity of developing individualized and area-specific charging networks to bolster utilization and enhance usability. As the first study, to the best of the authors' knowledge, to explore geographic variations in charging behavioral patterns, this study serves as a crucial stepping stone towards establishing an inclusive, user-centric, and accessible EVSE infrastructure for all.

EVSE Effectiveness in Multi-Unit Residential Buildings Using Composite Optimization and Heuristic Search

The effectiveness of electric vehicle supply equipment (EVSE) is a very important factor in multi-unit residential buildings (MRBs) when planning to invest in an electric vehicle (EV). However, the expected benefits depend on not only technology but also need many non-functional requirements such as building facilities, electrical infrastructure, operating costs, and energy demand management of EVSE. We discuss the functional and non-functional constraints in utilizing EVSEs in MRBs and addresses them by constructing a composite optimization problem with a heuristic boundary selection. The proposed model urges the use of electrical safety codes –to mitigate the hazard risk– and promotes deploying a flexible and scalable energy management system (EMS) to schedule, reserve, and tune the charging sessions. This article provides an effective EMS for mitigating the energy demand growth caused by EV charging on MRBs, by finding the equilibrium number of EVSEs and their energy usage through a heuristic search. The proposed EMS is reinforced by embedding machine learning tools such as k-means, silhouette scoring, heuristic search, and autoregressive model to adjust the optimal operational state of EVSEs. We delineated the proposed framework and the outcomes using two case studies with real data. The results showed that more EVSEs can be utilized in MRBs and 100% EVs can be fully charged with a lower capital cost and no additional energy demand cost.

TLS-handshake for Plug and Charge in vehicular communications

Electric vehicle technology has brought some important issues to order. Securing the communication between electric vehicle and charging station is an important one. The International Organization for Standardization released ISO 15118 standard to specify the communication between electric vehicles and electric vehicle supply equipment. The ISO 15118 standard requires Transport Layer Security function for secure charging communication between electric vehicle and charging station as mandatory. The Transport Layer Security requirements have been completely changed with the latest version of the standard (ISO 15118-20) and have not been clearly described and implemented yet. The implementation of the function causes an inevitable vulnerability due to non-functioning authentication resulting with the entire vehicle function and security system can suddenly stop working. For this reason, new Transport Layer Security protocol must urgently be analyzed, developed, integrated, and implemented.This study proposes solutions for the development, implementation, realization of Transport Layer Security handshake requirements and functions between electric vehicle and charging station with ISO 15118 protocol. The new and existing Transport Layer Security requirements, analyzed, evaluated and the new Transport Layer Security functions derived and fully described. Based on these requirements and functions, a Transport Layer Security communication sequence and processes are developed and implemented and validated on the test bench. The validation proved sufficient implementation of the Transport Layer Security functions (successful authentication, exchange of cipher suite parameters and generation of the TLS master key). The messages were prosperous encrypted and decrypted with the generated master key. Thus, Transport Layer Security handshake is developed, implemented, and validated with this study.

A Federated Byzantine Agreement Model to Operate Offline Electric Vehicle Supply Equipment

A Federated Byzantine Agreement Model to Operate Offline Electric Vehicle Supply Equipment

Revolutionizing mobility: a comprehensive review of electric vehicles charging stations in India

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.

A Geo‐Spatial Method for Calculating BEV Charging Inconvenience using Publicly Available Data

ABSTRACTAs governments and the automotive industry push towards electrification, it becomes increasingly critical to address the factors which influence individual car buying decisions. Evidence suggests that operational inconvenience or the perception thereof plays a large role in consumer decisions concerning battery electric vehicles (BEVs). BEV ownership inconvenience and its causal factors have been relatively understudied, rendering efforts to mitigate the issues insufficiently informed. This paper presents a method of producing an empirical equation which relates operational inconvenience to a small number of housing and local electric vehicle supply equipment (EVSE) infrastructure factors. The paper then further provides a method of applying the equation in a geo‐spatial context allowing for the evaluation of the effects of policies in a geographical manner. this method enables future quantitative analyses concerning investment in EVSE infrastructure to be directly sensitive to BEV operational inconvenience due to charging.

WIRELESS CHARGING STATION FOR EV VEHICLES AND SOLAR PANELS

Electric vehicles (EVs) are a new and developing technology in the power and transportation sectors. Regarding the state of the economy and ecology, there are more advantages. The most crucial component of electric vehicles is the charging station, which lowers environmental pollution and the influence of greenhouse gases. Electric Vehicle Supply Equipment is another name for this electric charging station (EVSE). It is made up of both low power and high power. It would be very helpful to build an on-road charging system with a solar panel so that we can charge at any time. We can also drive off-road with connected batteries because the high power is terminated at a fraction of the second charging that can be implemented in an electric vehicle rather than the low power. The photovoltaic (PV) cell's force from sunlight is transferred to the electric vehicle's battery via the application of remote force move technology. Sunoriented boards are thought to build an autonomous force station, so reducing its need on common energy resources. By using the light energy the sun produces, the sunoriented boards generate electrical energy. The energy obtained from the board is transferred to a battery by means of a solarpowered charge regulator, therefore increasing the photovoltaic cell's force output. Due to the wireless connection between the transmitting and receiving coils, DC current is injected into the battery. The battery is automatically switched off from solar power once it is full. As a consequence, electric battery utilization and sustainable mobility are achieved. There is an overview of the charging stations and a discussion of the implications of electric vehicles.

Supply Chain Transport Management, Use of Electric Vehicles, Review of Security and Privacy for Cyber-Physical Transportation Ecosystem and Related Solutions

The convergence of modern technology and supply chain operational dynamics has shaped the fabric of today’s freight transportation practice and made the role of electric vehicles (EVs) profoundly significant in regular use in business operations. In addition to the expanding prevalence of EVs and charging infrastructures for medium and heavy-duty supply chain transport systems, it challenges the business community for deployment purposes. Moreover, these intelligent transport systems for modern supply chain organizations delve into the heart of a transformative realm, offering opportunities for academics and practitioners to explore the tools, strategies, methodologies, and training operation managers that propel enterprises toward EV-driven operational excellence. This paper describes a reference map that relates to different interface types and consists of various categories of electric vehicle supply equipment (EVSE). The paper also reviews security and privacy threats associated with the reference map interfaces and relevant components and presents highlighted security protection solutions in academic literature.

Incremental Profitability Evaluation of Vehicle-to-Grid-Enabled Automated Frequency Restoration Reserve Services for Semi-Public Charging Infrastructure: A Case Study in Belgium

The current paper defines a framework for the introduction of automated frequency restoration reserve services, enabled by vehicle-to-grid technology, into the business model of an entity owning and operating a network of semi-public Electric Vehicle Supply Equipment. It assesses the profitability of this introduction by performing a case study based on the real-life electric vehicle charging data from the EVSE network located in a hospital parking lot. From the results of the study, it is clearly visible that the introduction of vehicle-to-grid-enabled automated frequency restoration reserve services has a significant positive incremental profitability; however, this is heavily dependent on the plug-in ratio of the charging network, determined by electric vehicle users’ behavior.

Energy Management Strategies of Solar Rooftop Campus with Battery Energy Storage System (BESS) And EV Supply Equipment (EVSE) using HOMER

Commercial sector has been among the largest source of electrical load demand in Malaysia including educational buildings. Nowadays, distributed energy resources, such as solar photovoltaics (PV) and battery energy storage systems (BESS), are being implemented in educational campus to save and manage its energy consumption. Additionally, electric vehicles (EV) are becoming more popular as they are more environmentally friendly than the traditional gasoline-powered cars. This research aims to examine the cost-effectiveness, environmental and technical aspects of a microgrid system that includes grid-connected solar panels, BESS and EV supply equipment (EVSE). The study was conducted for Universiti Teknologi MARA campus Pulau Pinang. The campus microgrid models are simulated using HOMER software to explore four different of microgrid configurations. The load profiles of the buildings in the campus were gathered and used in the model to identify the optimum microgrid model. The findings show Grid-PV-BESS has the best hybrid energy system based on the weightage sum decision making approach considering multiple criteria assessments. Through this study, a sustainable hybrid energy system in the educational campus can be proposed integrating solar PV, BESS and EVs.