Plug In Electric Vehicles in Smart Grids

The Plug-in Electric Vehicles (PEVs) are the Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs). PEVs will dominate the transportation in the personal mobility mode and in the automobile market by 2030. Widespread adoption of PEVs brings potential, social and economic benefits. The focus on promoting use of electric vehicles in road transportation is very essential to meet the climate change targets and manage the ever hiking prices of fast depleting fossil fuels. However, there are lots of uncertainties in the market about the acceptability of PEVs by customers due to the capital and operation costs and inadequate infrastructure for charging systems. The penetration level in the market is not encouraging, in spite of incentives offered by Governments. Manufacturers are also not sure of the market, even though predictions are strong and attractive. Major manufacturers, however, are already ready with their plans to introduce electric vehicles to mass market. The use of PEVs has both technological and market issues and impacts. Series of research works have been reported to address the issues related to technologies and its impacts on political, economic, environmental, infrastructural and market potential aspects. Works dealing with suitable infrastructure such as charging stations and use of smart grids are reported. These steps are aimed to bring down the capital and operational costs that are comparable to the costing of conventional transport vehicles. The penetration level of PEVs in transportation will accordingly increase and keep the climate targets met and conserve fossil fuels for use in other economic segments. An overview on these issues is presented in this chapter.

100 year old gasoline engine technology vehicles have now become one of the major contributors of greenhouse gases. Plug-in Electric Vehicles (PEVs) have been proposed to achieve environmental friendly transportation. Even though the PEV usage is currently increasing, a technology breakthrough would be required to overcome battery related drawbacks. Although battery technology is evolving, drawbacks inherited with batteries such as; cost, size, weight, slower charging characteristic and low energy density would still be dominating constrains for development of EVs. Furthermore, PEVs have not been accepted as preferred choice by many consumers due to charging related issues. To address battery related limitations, the concept of dynamic Wireless Power Transfer (WPT) enabled EVs have been proposed in which EV is being charged while it is in motion. WPT enabled infrastructure has to be employed to achieve dynamic EV charging concept. The weight of the battery pack can be reduced as the required energy storage is lower if the vehicle can be powered wirelessly while driving. Stationary WPT charging where EV is charged wirelessly when it is stopped, is simpler than dynamic WPT in terms of design complexity. However, stationary WPT does not increase vehicle range compared to wired-PEVs. State-of-art WPT technology for future transportation is discussed in this chapter. Analysis of the WPT system and its performance indices are introduced. Modelling the WPT system using different methods such as equivalent circuit theory, two port network theory and coupled mode theory is described illustrating their own merits in Sect. 2.3. Both stationary and dynamic WPT for EV applications are illustrated in Sect. 2.4. Design challenges and optimization directions are analysed in Sect. 2.5. Adaptive tuning techniques such as adaptive impedance matching and frequency tuning are also discussed. A case study for optimizing resonator design is presented in Sect. 2.6. Achievements by the research community is introduced highlighting directions for future research.

Plug-in electric vehicles (PEVs), as a major component of Smart Grid technologies, can achieve high energy efficiency, reduce carbon emissions, spur high-technology innovation, and ensure a reliable energy supply. An ever-increasing number of PEVs will radically change the traditional views of the power and transportation industries, the social environment, and the business world. The electrification of transportation brings both opportunities and challenges to existing critical infrastructures. This book chapter takes the position that the successful rollout of PEVs depends highly on the affordability, availability, and quality of the associated services that the nation’s critical infrastructures can provide (e.g., a PEV charging facility at a parking lot). There is an urgent need to accelerate the design, development, and deployment of cost-effective, reliable, and customer-friendly PEV charging infrastructures. This chapter presents a comprehensive overview of the planning, control, and management aspects of PEV parking lots in a Smart Grid environment.

It is of great importance to smart grids to build a communications network that can support the future power utility growth, customer connections, and new applications. Relying on advanced communications and broadband access technologies, power utilities are moving towards distribution grid modernization to optimize energy utilization. One significant main concern is the integration of plug-in electric vehicles (PEVs) within smart grids. This chapter provides a comprehensive performance evaluation of PEV coordination strategies over integrated Fiber-Wireless (FiWi) smart grid communications infrastructures using a scaled-down testbed and advanced co-simulator. As the coordination of PEVs was not experimentally demonstrated previously, this chapter describes a smart grid testbed based on a real-world distribution network in Denmark by scaling a 250 kVA, 0.4 kV real low-voltage distribution feeder down to 1 kVA, 0.22 kV. The architecture of the power and communications networks, the scaling-down process, and its main functionalities are described. Furthermore, a novel centralized PEV scheduling and decentralized coordination mechanism is proposed. The obtained experimental results show that the proposed hybrid centralized and decentralized control approach for PEV charging simultaneously takes into account the charging cost, network congestion, and local voltage. Moreover, the coordination between distribution management system (DMS) and sensors is realized in real-time using the developed smart grid testbed (SGT) by the synchronized exchange of power and control signals via a heterogeneous Ethernet-based mesh network. The developed SGT is a step forward to (i) identify practical problems and (ii) validate and test new smart grid mechanisms under realistic physical conditions. However, building such a testbed is time and space consuming. To evaluate large-scale smart grid systems, co- and multi-simulation experiments may be carried out instead. Therefore, the chapter next presents the co-simulation of a power distribution system combined with a smart grid communications infrastructure in order to enable real-time exchange of information between PEVs and utilities for the coordination of charging algorithms, which allow PEVs to intelligently consume or send stored power back to the grid (Vehicle-To-Grid capability). Different types of coordinated PEV charging algorithms in a multidisciplinary approach by means of co-simulation of both power and communication perspectives are implemented. A comparison of both centralized and decentralized PEV charging algorithms is drawn in terms of power and communication performance. The integration of photovoltaic solar panels to locally charge PEVs, which plays a major role in limiting the impact of PEV charging on the utility grid and thereby minimizing peak energy demand as well as effectively achieving load balancing, is also investigated.

With emerging penetration of Plug-in Electric Vehicles (PEVs) into smart grids, system operators face new challenges regarding the system security. The security involves all parties in the energy system, because PEVs are not only considered as loads, but also as demand response or distributed energy resources, with bidirectional power flow into the distribution network. Furthermore, due to the random time, amount and location of the PEVs utilization, their behavior is inherently uncertain. In this context, monitoring and control of PEVs utilization necessitate the real-time data communication with control centers throughout the smart grid. The security and reliability of power system will be dependent on how the PEVs data are collected and managed. Hence, assuring data confidentiality, integrity and availability are significant parts of PEV-integrated cyber-physical systems (CPS). This chapter aims at exploring the cyber security issues of PEVs in the smart grid and review some of the state-of-the-art analysis methods to detect the cyber-attacks. We study the model-based and signal-based intrusion detection methods to detect any anomalies, followed by a specific application to PEVs false data injection in the smart grid. The chi-square test and discrete wavelet transform (DWT) are used for anomaly detection.

The aim of this chapter is to expose the probabilistic Plug-in electric vehicle (PEV) charging model and to apply it in a distribution grid to evaluate the PEV impact. The model is based on agent-based techniques, has probabilistic variables, includes queuing theory, and applies Monte Carlo methodology. The PEV user’s charging needs can be divided in two categories: private charging points and public charging points. Regarding private charging points, the PEV charging demand depends strongly on private user’s mobility needs and it includes variables as number of trips per day, driving distance, and arrival time. Also, the user’s profile can be modelled with probabilistic variables as the PEV model and the charging connection point. All these variables can be modelled with probabilistic distributions functions to obtain a probabilistic model with data from different sources. Additionally, public charging points are made available for PEV users that need to plug-in the vehicle between trips to extend the vehicle autonomy. After that, the model is applied to a case study to analyze the impact to the power network. Probabilistic grid impact includes the probability to exceed a maximum voltage drop, and transformer and current saturations. The main impact is on saturations of lines and they can be reduced controlling private points but it does not make sense to control the public points. Fast chargers present some challenges for grid integration because they are public charging points of 50 kW power rate per charger. In this chapter, a stochastic arrivals model is applied to analyze the public fast charging stations, the PEV user’s charging needs and their grid impact. Fast charging stations are designed to extend the autonomy of PEV and their arrivals to the station have a certain stochastic behavior. The probabilistic arrivals for the fast charger impact evaluation are based on queuing theory and the corresponding electricity demand is evaluated. The case study analyzed includes three fast chargers installed in the same grid and they provoke saturations in lines.

The strategy of using Plug-in Electric Vehicles (PEVs) for vehicle-to-grid (V2G) energy transfer in a smart grid environment can offer grid support to distribution utilities, and opens a new revenue opportunity for PEV owners. V2G has the potential of reducing grid operation costs in demand-constrained urban feeders where peak-electricity prices are high. Photovoltaic (PV) solar energy conversion can also assist urban distribution grids in shaving energy demand peaks when and where there is a good match between the solar irradiation resource availability and electricity demands. This is particularly relevant in urban areas, where air-conditioning is the predominant load, and on-site generation a welcome resource. Building-integrated photovoltaics (BIPV) plus short-term storage can offer additional grid support in the early evening, when solar irradiation is no longer available, but loads peak. When PEVs become a widespread technology, they will represent new electrical energy demands for generation, transmission and distribution (GT&D) utilities. PEVs that are parked in the early evening can play the role of short-term energy storage devices for PV electricity generated earlier in the day. In a smart-grid environment, the combination of PEVs and PV can offer a good solution to assist the public grid. In this chapter, results on analyses of these strategies applied to selected urban feeders in the metropolitan area of a capital city in Brazil are presented. It is shown that, in a smart-grid environment, it should be possible to accommodate PEVs, BIPVs, V2G and the recharging of PEVs (grid-to-vehicle—G2V), and at the same time assist the urban grids and supply the new energy demands represented by the introduction of a PEV fleet, without compromising the existing grid infrastructure.

A global resurgence of electric vehicle has taken place as a sustainable alternative to fossil fuel dependent transportation. As a result, the new plug-in electric vehicle (PEV) charging load is emerging into power networks. Even though the environmental and economic benefits of electrified transportation are very much apparent, its impacts on power systems still need to be understood. This chapter develops a mathematical model of the PEV charging load, evaluates its impact on system steady state voltage stability and suggests effective remedies to overcome the stability impacts due to PEV charging on power grids. Load characteristics profoundly influence the static voltage stability of power systems. Therefore, it is important to understand the characteristics of this emerging PEV charging load and its impact on power system voltage stability. Hence, a load model for the power electronically controlled PEV battery charging load is introduced in this chapter. The proposed PEV load model consists of a combination of a constant power load and a voltage dependent load having negative exponential characteristics. Due to the voltage dependent characteristics of PEV, the conventional power flow equations require modifications in order to accommodate the PEV load. The required modifications to the Newton Raphson power flow algorithm are described in this chapter. The system studies carried out in this chapter found that PEV charging load cause negative impact on system voltage stability, hence effective remedial measures are introduced. Further, a computationally efficient index which has good physical interpretation is introduced for identifying voltage stability considered charging infrastructure.

The integration of a massive number of small-scale wind turbines and plug-in electric vehicles (PEVs) brought about urgent technical challenge to power distribution network operators (DNOs) in terms of secure power supply and energy dispatching optimization. In this chapter, we exploited three coordinated wind-PEV energy dispatching approaches in the Vehicle-to-Grid (V2G) context, i.e. valley searching, interruptible and variable-rate energy dispatching, aiming to promote the user demand response through optimizing the utilization efficiency of wind power generation as well as meeting the dynamic power demands. This issue is addressed in a stochastic framework considering the uncertainties of wind power generation as well as the statistical PEV driving patterns. The performance of the proposed solutions is assessed through a comparative study through numerical simulation experiments covering sufficient system scenarios by the use of scenario generation and reduction techniques. The result demonstrates that the energy dispatch based on the latter two approaches can achieve better matching between power generation and demands as well as PEV user satisfaction. In addition, the suggested approaches can be adopted by DNOs in practice with minimal deployment hurdles to promote the energy supplies within microgrid with wind power sources and PEVs.

Balancing loads in low voltage networks is a challenging task due to a continuous fluctuation in the power demand. Voltage unbalance is a condition in which the voltage phasors differ in amplitude and/or do not have its normal 120° phase relationship. This has a potential to introduce technical issues that lead to a costly phenomenon for power distribution system due to the high penetration of Plug-in Electric Vehicles (PEVs). Voltage unbalance study is essential as the propagation of zero sequence component in the distribution system is limited by transformer winding connections and network grounding. Indeed, single phase loads are not affected by unbalance unless the unbalance causes over or under voltages which exceed the acceptable limits. However, the large numbers of PEVs charging from single phase residential feeders of distribution networks may exceed the statutory limits. This chapter presents theoretical discussion with analytical framework for modeling the effects of voltage unbalances due to PEV penetration. A PEV charging profile of a conventional PEV battery has been employed with the daily load demand to synthesize the dynamic effect of PEV penetration. A distribution network topology has been used with unbalanced allocation of single-phase loads and PEVs connected in four-wire, three phase network to investigate the effects of PEV charging on the feeders subject to voltage unbalance. Furthermore, the chapter explores the application of PEV load balancing strategy in the context of smart grid to mitigate the effects of unbalanced allocation of PEVs.

Plug-in Electric Vehicles (PEVs) will remain connected to the grid a high percentage of their life-time. During these connections, idle-time will be considerably longer than battery charging time. This fact turns PEV idle-time into a suitable candidate to help in the distribution grid management by implementing active distribution grid functions, leading to the future Smart Grids. In this chapter, conventional ancillary services for distribution grids are presented, including their development in the new context of Distributed Energy Resources (DER), micro grids, smart grid and either in connected or isolated modes. Later, the coordination of the previously discussed services with PEVs is analyzed, mainly considering them as Energy Storage Systems. Then, the optimization problem is presented, empathizing the indexes and constriction that could be taken into account. From the optimization procedure, reference operation setpoints are generated for each individual PEV. Then, the coordination of charger operations for maximizing global impact on the whole distribution grid is developed. Control strategies are presented and analyzed in terms of their operation setpoints in normal and abnormal grid states, when they are expected to control active, reactive and harmonic power. Finally, some examples on how the described strategies can be used for controlling active, reactive and harmonic power using a PEV charger, when the PEV is following the given operation references, are discussed.