Secure and privacy-aware proxy mobile IPv6 protocol for vehicle-to-grid networks

Vehicle-to-Grid (V2G) networks have emerged as a new communication paradigm between Electric Vehicles (EVs) and the Smart Grid (SG). In order to ensure seamless communications between mobile EVs and the electric vehicle supply equipment, the support of ubiquitous and transparent mobile IP communications is essential in V2G networks. However, enabling mobile IP communications raises real concerns about the possibility of tracking the locations of connected EVs through their mobile IP addresses. In this paper, we employ certificate-less public key cryptography in synergy with the restrictive partially blind signature technique to construct a secure and privacy-aware proxy mobile IPv6 (SP-PMIPv6) protocol for V2G networks. SP-PMIPv6 achieves low authentication latency while protecting the identity and location privacy of the mobile EV. We evaluate the SP-PMIPv6 protocol in terms of its authentication overhead and the information-theoretic uncertainty derived by the mutual information metric to show the high level of achieved anonymity

Unification requirements of electric vehicle charging infrastructure

By increasingelectric vehicles in numbers and getting the public attention, availability, safety and accessibility of its charging infrastructure are key factorsto users’ satisfaction. Charging infrastructure in electric vehicle industry can have a role as an interface for exchanging information among other components as well. Currently, lack of universality in electric vehicle industry has caused anisolation in networks of electric vehicles. This isolationwill cause difficulty in having an aggregated set of information about electric vehicles and their consumption pattern. The paper reviews current charging infrastructure and the possibility of providing universality based on candidate protocols and technologies. © 2016 Institute of Advanced Engineering and Science

Secure and privacy-aware proxy mobile IPv6 protocol for vehicle-to-grid networks

Vehicle-to-Grid (V2G) networks have emerged as a new communication paradigm between Electric Vehicles (EVs) and the Smart Grid (SG). In order to ensure seamless communications between mobile EVs and the electric vehicle supply equipment, the support of ubiquitous and transparent mobile IP communications is essential in V2G networks. However, enabling mobile IP communications raises real concerns about the possibility of tracking the locations of connected EVs through their mobile IP addresses. In this paper, we employ certificate-less public key cryptography in synergy with the restrictive partially blind signature technique to construct a secure and privacy-aware proxy mobile IPv6 (SP-PMIPv6) protocol for V2G networks. SP-PMIPv6 achieves low authentication latency while protecting the identity and location privacy of the mobile EV. We evaluate the SP-PMIPv6 protocol in terms of its authentication overhead and the information-theoretic uncertainty derived by the mutual information metric to show the high level of achieved anonymity

Secure and Privacy-Aware Proxy Mobile IPv6 Protocol for Vehicle-to-Grid Networks

Vehicle-to-Grid (V2G) networks have emerged as a new communication paradigm between Electric Vehicles (EVs) and the Smart Grid (SG). In order to ensure seamless communications between mobile EVs and the electric vehicle supply equipment, the support of ubiquitous and transparent mobile IP communications is essential in V2G networks. However, enabling mobile IP communications raises real concerns about the possibility of tracking the locations of connected EVs through their mobile IP addresses. In this paper, we employ certificate-less public key cryptography in synergy with the restrictive partially blind signature technique to construct a secure and privacy-aware proxy mobile IPv6 (SP-PMIPv6) protocol for V2G networks. SP-PMIPv6 achieves low authentication latency while protecting the identity and location privacy of the mobile EV. We evaluate the SP-PMIPv6 protocol in terms of its authentication overhead and the information-theoretic uncertainty derived by the mutual information metric to show the high level of achieved anonymity

An independent protocol supporting real-time cross-network authentication in electric vehicles' network

The absence of charging infrastructure has been highlighted by several researchers as an obstacle in electric vehicle (EV) industry. However, less attention has been drawn to user access to existing charging infrastructure. Therefore, this research investigated the practical methods of increasing accessible charging stations to EV users. EV Service Providers (SP) and EV Networks have been established to provide charging facilities for EV users. However, the business model and method of identifying users have formed a group of closed networks performing in isolation. Despite the availability of charging stations, the isolation of EV networks prevents users from charging their EVs which has created a barrier against the development of EV industry and affected the general acceptance of EVs. Thus, this research aimed at formulating an operational framework which involved a proposed Inter-Service Provider Charging Protocol (ISPCP) that aimed to provide a peer-to-peer communication among networks of charging stations and supports cross-network charging capability for EV users. The framework consisted four phases: review of existing works, development of a protocol, development of a RESTFul WEB API using the protocol, and evaluation of the protocol using the API. To develop the protocol, current state of the art in the networks of EV charging stations was reviewed. In addition, a systematic literature review (SLR) was conducted to investigate the causes and effects of range anxiety and to extract the existing solutions. ISPCP has been implemented, deployed, and tested using a RESTFul WEB API in order to evaluate its feasibility and effectiveness in which performance, response time, and cost were measured and identified as its effectiveness metrics. Findings of the study showed a faster response time of 9.4 seconds which is considered to be a 59.24% improvement when compared to similar protocols. The results obtained in the study provide support for feasibility of ISPCP as it has been proven to increase the number of charging stations accessible to EV users by providing cross-network charging solutions

Pairing-based authentication protocol for V2G networks in smart grid

[EN] Vehicle to Grid (V2G) network is a very important component for Smart Grid (SG), as it offers new services that help the optimization of both supply and demand of energy in the SG network and provide mobile distributed capacity of battery storage for minimizing the dependency of non-renewable energy sources. However, the privacy and anonymity of users¿ identity, confidentiality of the transmitted data and location of the Electric Vehicle (EV) must be guaranteed. This article proposes a pairing-based authentication protocol that guarantees confidentiality of communications, protects the identities of EV users and prevents attackers from tracking the vehicle. Results from computing and communications performance analyses were better in comparison to other protocols, thus overcoming signaling congestion and reducing bandwidth consumption. The protocol protects EVs from various known attacks and its formal security analysis revealed it achieves the security goals.Roman, LFA.; Gondim, PRL.; Lloret, J. (2019). Pairing-based authentication protocol for V2G networks in smart grid. Ad Hoc Networks. 90:1-16. https://doi.org/10.1016/j.adhoc.2018.08.0151169

Efficient, Secure and Privacy-Preserving PMIPv6 Protocol for V2G Networks

To ensure seamless communications between mobile Electric Vehicles (EVs) and EV power supply equipment, support for ubiquitous and transparent mobile IP communications is essential in Vehicle-to-Grid (V2G) networks. However, it initiates a range of privacy-related challenges as it is possible to track connected EVs through their mobile IP addresses. Recent works are mostly dedicated to solving authentication and privacy issues in V2G networks in general. Yet, they do not tackle the security and privacy challenges resulting from enabling mobile IP communications. To address these challenges, this paper proposes an Efficient, Secure and Privacy-preserving Proxy Mobile IPv6 (ESP-PMIPv6) protocol for the protection of mobile IP communications in V2G networks. ESP-PMIPv6 enables authorised EVs to acquire a mobile IPv6 address and access the V2G network in a secure and privacy-preserving manner. While ESP-PMIPv6 offers mutual authentication, identity anonymity and location unlinkability for the mobile EVs, it also achieves authorised traceability of misbehaving EVs through a novel collaborative tracking scheme. Formal and informal security analyses are conducted to prove that ESP-PMIPv6 meets these security and privacy goals. In addition, via a simulated assessment, the ESP-PMIPv6 is proven to achieve low authentication latency, low handover delay, and low packet loss rate in comparison with the PMIPv6 protocol

Optimal behavior of a PEV parking lot in renewable-based power systems

There have been a lot of developments in terms of Plug-in Electric Vehicles (PEVs) regarding many different subjects, and with some variations between authors. On this basis, it is intended to sum up a lot of contents being approached, and help understanding them. Followed by the development and analysis of a model in order to better understand the functionality of these new developments. First a state of the art is presented where the new development are presented, these will include management of the PEV’s, uncontrolled or controlled (i.e. aggregated) and their capability of using V2G and G2V technologies are analyzed. Afterwards, electricity markets are approached where real world applications are shown and different market types are categorized in order to a better understanding of the subject. The interaction of the PEVs with some renewable energy resources (e.g. solar, wind and biomass) is presented. To finalize, models of PEVs are categorized and multiple types of modules, the related variables, applied methods, and the considered parameters are presented. For a case analysis, a model that includes a parking lot of PEVs will be studied, which includes renewable energy resources, wind and solar. The objective is to analyze the impact of these on the market participation of the parking lot and also on the distribution grid. These analyses will be made on size variations, grid placement and also constraint variations of the model.Tem havido muitos desenvolvimentos em relação a veículos elétricos com tecnologia Plug-in (PEVs), sendo um tema abrangente com bastantes tópicos a serem estudados, sendo que existem também diferentes abordagens do tema por diferentes autores. Tendo isto em consideração, o objetivo inicial será a recolha de informação relativo a esta área e a sua sumarização de modo a possibilitar uma maior compreensão sobre a área. De seguida, o modelo desenvolvido será efetuada a sua análise, tendo em consideração alguns destes desenvolvimentos mencionados previamente. Primeiramente um estado da arte será apresentado onde os recentes desenvolvimentos na área serão apresentados. Estes desenvolvimentos incluem a possibilidade de gestão e manuseamento dos veículos, controlados ou descontrolados (i.e. agregador), e a possibilidade da utilização das tecnologias veiculo para a rede (V2G) e rede para o veículo (G2V) é analisada. De seguida, são analisado os mercados de energia onde serão apresentados casos reais e diferentes tipos de Mercado serão descriminados. A interação dos PEVs com algumas energias renováveis (e.g. Solar, Vento e biomassa) é apresentada. Finalizando modelos de PEVs serão categorizados fazendo distinção entre eles, entre tipo de modelos, variáveis, métodos aplicados, e os parâmetros considerados por estes mesmos. Como caso de estudo é apresentada a análise de um modelo que conta com um parqueamento de PEV, inclui energias renováveis. O objetivo é o de analisar os efeitos das energias renováveis na participação do mercado do parqueamento e o impacte na rede de distribuição. Esta análise será feita pela variação na potência instalada das renováveis, localização na rede do parqueamento e variação nas limitações do modelo

Electric Vehicle - Smart Grid Integration: Load Modeling, Scheduling, and Cyber Security

The modern world has witnessed the surge of electric vehicles (EVs) driven by government policy worldwide to reduce transportation’s dependence on fossil fuels. According to (Slowik, 2019), the global EV market has grown sharply with the annual light-duty EV sales surpassing 2 million in 2018, which is about a 70% increase from 2017. The increase in EV population implies the rise in energy demand, and that introduces new challenges to the electricity sector. EV charging load demand in high penetration scenarios, which is foreseen, may lead to stability and quality issues in power grids. Generation capacity and the electricity infrastructure upgrade may be required to address those issues; however, it increases generation costs significantly. The most common EV chargers installed today deliver around 7 kW of power, which is over four times that of an average household power consumption in the US. EV charging load often shows two peaks in a day, one in the morning when people plug in the EV at the workplace and the other in the evening when people get home from work. Without proper energy management for EV charging, the vast power demand due to a large number of plugged-in EVs can stress the electric grid, degrade the electric power quality, and impact the wholesale electricity market. Although an EV battery may store energy up to 80 kWh, which requires more than 10 hours to charge at 7kW from empty, we found that most EVs need only 12 kWh per charge or 1.7 hours at 7 kW to meet daily commute requirement while they stay in the parking garage for a more extended period. This implies that EVs can have considerable time-flexibility for charging, and it is not necessary to start chargingright after plugging in, which is likely to result in the charging power add-up. A proper EV charging schedule can well allocate the charging load to prevent power peaks. Therefore, EV charging scheduling can play a significant role in mitigating the adverse effects of vast EV charging demand without upgrading the power grid capacity.To optimize the EV charging schedule while satisfies EVs’ charging demand, each EV’s stay duration and energy need are essential parameters for the optimization. Those parameters are based on predictions to minimize human intervention. Nonetheless, the uncertainty of EV user behavior poses a challenge to the prediction accuracy. Therefore, this dissertation demonstrates an ensemble machine learning-based method to model and predict the EV loads accurately, thereby improving the performance of EV charging scheduling.On the other hand, this smart EV-grid integration, which requires massive communication, including collecting, transmitting, and distributing real-time data within the network, makes it more susceptible to cyber-physical threats. Potential breaches could not only affect grid operation but also reduce consumers’ willingness to adopting EVs over conventional fuel-powered vehicles. This dissertation also presents the vulnerability analysis and risk assessment for a smart EV charging system to develop the countermeasures to secure the network. Also, while it is inevitable that the security has flaws, this dissertation provides a novel anomaly detection approach based on the invariant correlations of different measurements within the EV charging network