Integration of Electric Vehicles in the Electric Power System

Energy consumption in the field of transportation comes next to industrial consumption worldwide. If transportation is completely powered by renewable energy, the utilization of fossil fuels can be drastically reduced, which will result in a lesser amount of greenhouse gas emissions. Electric vehicles (EVs) can act as an alternative to make transportation pollution-free. Large-scale usage of EVs causes high electricity demand on the supply system. This problem can be overcome by utilizing renewable energy sources (RESs) for Electric Vehicle charging. Due to the unpredictability of RESs, coordinating EV charging with other loads and renewable generation is problematic. By using EVs as energy units, power fluctuations in the electric grid can be compensated. This paper presents a summary of recent research in the domain of integration of electric vehicles (EVs) to the smart grid. Electric vehicles-smart grid integrated systems face several issues related to communication, grid infrastructure and control in the future power system. Smart grid technologies are summarized in Section 2. The existing research articles in this area are classified into two based on the purpose: EVs integration into the electric grid and Vehicle to grid services. Finally, the research gaps and future scope of incorporating electric vehicles with renewable energy sources and the Smart grid are highlighted.

Grid integration of Electric Vehicles (EVs) and renewable generation are major operational challenges for System Operator (SO) due to their respective mobility behavior dynamics and intermittent behavior. To deal with these challenges, an EV Aggregator (EVA) can employ Vehicle-to-Grid (V2G) technology to synergize grid integration of renewable energy resources (RESs) and EVs. EVA provides smart coordination between SO and EV owners providing grid support services through V2G charge/discharge scheduling of EVs. However, energy market prices uncertainties involved in market operation would significantly affect profit and behavior of EVA. Proposed work models an integrated DR and risk-aversive V2G scheduling of EVA for its expected profit maximization and effective utilization of photovoltaic (PV) generation from rooftop solar charging park incentivizing EV owners and flexibility enhancement to SO. Revenue of EVA is due to regulation and charging services to SO and EV owners respectively. The operational cost of EVA considers procurement cost of charging energy from wholesale electricity market and cost of battery degradation while ensuring EV owners’ driving requirements. The CVaR index is utilized for measuring EVA's risk. Results validate efficacy of proposed model and impact analysis of DR integration on electricity market operations of EVA through performance metrices.

• Presents the detail involvement of key stakeholders (DNOs, EOs, and CSOs) in EV integration. • Discusses the EV technology and grid integration in details. • Reviews on power management and optimization. • A case study outlining the status and future-plans for EVs in Western Australia. • Provides recommendations from stakeholder's perspective. In recent years, research on Electric Vehicles (EVs) has gained considerable attention due to their potential to reduce reliance on fossil fuels and curb environmental pollution significantly. Various stakeholders play a pivotal role in the large-scale EV integration into the existing power grid by providing unique services, particularly in grid power management and charging of EV. This study provides a comprehensive analysis of the critical role played by key stakeholders in the large-scale integration of electric vehicles (EVs) into the power grid, with a particular focus on grid power management and charging infrastructure. It systematically examines the involvement of Distributed Network Operators (DNOs), EV Owners (EOs), and Charging Station Owners (CSOs), elucidating their respective objectives, responsibilities, and challenges. Furthermore, the paper delves into power management strategies, reactive power regulation, and advanced control methodologies aimed at enhancing grid stability. A case study on EV adoption in Western Australia is presented to contextualize current developments and future trajectories. The study concludes by identifying key challenges associated with EV-grid integration and providing strategic recommendations to facilitate a more resilient, efficient, and sustainable power system.

Electric vehicles were proposed as a good solution to solving energy crisis and environmental problems caused by the traditional internal combustion engine vehicles. In the last years due to the rapid development of the electric vehicles, the problem of power grid integration was addressed. In order to not put additional pressure onto the power grid several new technologies were developed. This chapter presents the smart grid technology, vehicle-to-grid concept, and electric vehicles grid integration. These technologies made possible the integration of electric vehicles without any major changes in the power grid. Moreover, electric vehicles integration brought new benefits to the power grid like better integration of renewable energy.

Electric vehicles were proposed as a good solution to solving energy crisis and environmental problems caused by the traditional internal combustion engine vehicles. In the last years due to the rapid development of the electric vehicles, the problem of power grid integration was addressed. In order to not put additional pressure onto the power grid several new technologies were developed. This chapter presents the smart grid technology, vehicle-to-grid concept, and electric vehicles grid integration. These technologies made possible the integration of electric vehicles without any major changes in the power grid. Moreover, electric vehicles integration brought new benefits to the power grid like better integration of renewable energy.

Emissions from the internal combustion engine (ICE) vehicles are one of the primary cause of air pollution and climate change. In recent years, electric vehicles (EVs) are becoming a more sensible alternative to these ICE vehicles. With the recent breakthroughs in battery technology and large-scale production, EVs are becoming cheaper. In the near future, mass deployment of EVs will put severe stress on the existing electrical power system (EPS). Optimal scheduling of EVs can reduce the stress on the existing network while accommodating large-scale integration of EVs. The integration of these EVs can provide several economic benefits to different players in the energy market. In this paper, recent works related to the integration of EV with EPS are classified based on their relevance to different players in the electricity market. This classification refers to four players: generation company (GENCO), distribution system operator (DSO), EV aggregator, and end user. Further classification is done based on scheduling or charging strategies used for the grid integration of EVs. This paper provides a comprehensive review of technical challenges in the grid integration of EVs along with their solution based on optimal scheduling and controlled charging strategies.

Electric vehicles standards, charging infrastructure, and impact on grid integration: A technological review

Flexible Integration of EVs and PVs into the Electricity Grid

The operational aspects of future power systems are expected to be influenced significantly by the increasing grid integration of electric vehicles (EVs). This study analyzes the impact of EVs on future power systems and investigates the enabling technologies to facilitate higher EV integration into the electricity grid. On this note, a thorough literature review on the existing grid challenges has been performed and associated enabling technologies have been identified. Based on the EV charging profiles, EV loading patterns were extracted and analyzed. The resulting EV loading profiles have then been overlaid on commercial/residential loading profiles to demonstrate the impact of widespread EV charging stations on the electricity network. This study has then investigated the voltage violation issues on a power network and the reduction of voltage violation by employing load shifting, network reconfiguration, renewable integration and battery storage. The implementation of the selected EV enabling technologies demonstrates significant improvement in the system voltage profile where the effectiveness of the enabling technologies would depend on the types of system loading patterns.

Recently, there has been an increase in the grid integration of electric vehicles (EVs) and solar photovoltaic (PV) systems, primarily driven by two goals: lowering energy costs and decreasing emissions. Numerous research studies have concentrated on the separate effects of integrating PVs and EVs into the grid. Nevertheless, it is important to recognize that as the adoption of PVs and EVs continues to grow, the supply grid will face the cumulative effects of PV and EV integration on power quality (PQ) challenges. To provide a comprehensive understanding, this study examines the joint impact of PVs and EVs on PQ aspects in detail. This study has indicated that EVs and PVs alone can adversely impact grid reliability and PQ because of the variable character of PV source and the unpredictability of EV demand. But multiple research efforts have shown that coordination between PVs and EVs can help to alleviate certain problems that arise from their individual integration. This study demonstrates PQ enhancement in a grid system integrated with PV and EV using a multilayer perceptron neural network (MLPNN) approach. In the system with PV integration, the GWO-ANFIS, MPPT technique is employed for optimizing power extraction. Under balanced non-linear loading conditions, simulation results show that the THD is initially 25.97% without compensation, then decreases to 12.57% with a shunt passive filter (SPF), 3.37% with the application of recursive least squares (RLS), and 1.37% with MLPNN. With much lower THD and quicker convergence, the suggested MLPNN-based controller exhibits improved harmonic mitigation. A comparison between the proposed and existing methods are drawn using the MATLAB/Simulink platform.

The ever-increasing number of plug-in electric vehicles (PEVs) requires appropriate electric vehicle grid integration (EVGI) for charging coordination to maintain grid stability and enhance PEV user convenience. As such, the widespread adoption of electric mobility can be successful. EVGI is facilitated through charging stations and empowers PEV users to manage their charging demand by using smart charging solutions. This makes PEV grids assets that provide flexibility to the power grid. The Internet of Things (IoT) feature can make smooth EVGI possible through a supporting communication infrastructure. In this regard, the selection of an appropriate communication protocol is essential for the successful implementation of EVGI. This study assesses the efficacy of the UK’s 4G network with TCP and 4G UDP protocols for potential EVGI operations. For this, an EVGI emulation test bed is developed, featuring three charging parking lots with the capacity to accommodate up to 64 PEVs. The network’s performance is assessed in terms of data packet loss (e.g., the data-exchange capability between EVGI entities) and latency metrics. The findings reveal that while 4G TCP often outperforms 4G UDP, both achieve latencies of less than 1 s with confidence intervals of 90% or greater for single PEV cases. However, it is observed that the high penetration of PEVs introduces a pronounced latency due to queuing delays in the network including routers and the base station servers, highlighting the challenges associated with maintaining efficient EVGI coordination, which in turn affects the efficient use of grid assets.

The electrification of transportation has become a sustainable solution to the global economic and environmental challenges associated with the fossil fuel-dependent transportation. Substantial electric vehicle (EV) integration has resulted in the recent past owing to the distinct advantages and various incentives provided by governments. It can be expected that EV penetration will further accelerate along with technological advancements. This strategic shift of primary source of transportation energy from oil pipelines to power grids will inevitably bring numerous challenges to power grids around the world. The potential impacts of EV integration on power grids are yet to be discovered. This research concentrated on modelling the EV charging load, evaluating its impact on power system stability and identifying remedies. Further, two computationally efficient indexes were developed to identify voltage stability and oscillatory stability prudent charging solutions. A comprehensive EV charging infrastructure planning strategy was also developed. This research investigated the probable grid impacts associated with EV charging by comprehensively reviewing the available literature. Even though there were number of system studies on wide variety of grid impacts, scant attention has been paid to impact of EV charging on system stability. Electrification of transportation brings significant load integration to the grid. Hence, it is important to understand the EV charging impact on power system stability. The extant literature is largely based on conventional load characteristics rather than actual EV load behaviours, due to the unavailability of proper load models. Hence, this study develops static and dynamic EV load models following analytical and numerical methodologies, as an essential basis for accurate system stability studies. It is identified that the static load model of a power electronically controlled EV load can be best described by a combination of constant power and negative exponential load models. The factors affecting the load model parameters are also evaluated. Subsequently, a dynamic load model is derived, considering the dynamics of the EV charger and the battery. The EV charging load dynamics could be described by an eleventh order dynamic model. The developed static and dynamic load models are then utilised to evaluate the impacts of EV charging on power system voltage stability and oscillatory stability. Power system static voltage stability and oscillatory stability studies with EV charging loads are carried out on different test systems, under several practical scenarios. The results show that the EV is an onerous load, and the existing studies which have modelled EVs with conventional load characteristics have resulted in conservative outcomes. Further investigations are performed iv | P a g e to identify the factors affecting the voltage stability and oscillatory stability of the power grid in the presence of the EV charging load. Remedies which can be implemented to mitigate impact of EV charging load on static voltage stability are investigated. Effectiveness of load bus voltage control to mitigate the voltage stability impact of EV charging load, is tested and verified. In addition, importance of giving priority to implement public charging stations to ease the grid impacts caused by distributed home based chargers in the distribution system, is highlighted in this research. It is found that proper planning can be done to minimise the grid impacts, proactively. Two computationally efficient indexes are derived to identify the relative static voltage stability and oscillatory stability status of the power system in different planning cases. The developed indexes having good physical interpretations are proven to be simple and easy to incorporate in distribution system planning exercises to obtain a stability preserved planning solution. A metaheuristic technique has been incorporated to facilitate EV charging infrastructure planning. Several planning cases are discussed to represent different planning requirements. A comprehensive EV charging infrastructure planning framework is developed by incorporating consumer, investor and power grid requirements within the planning objectives and constraints. This could identify solutions which cause less impact on the grid in terms of losses, voltage regulation, asset overloading, grid voltage stability and oscillatory stability, while optimally satisfying the EV customer and investor requirements. The optimal capacity and placement of a fixed capacitor to minimise grid impacts through effective reactive power compensation have also been identified. Further, the possibility of enhancing EV charging facilities while minimising the grid impacts is proven with optimum utilisation of renewable energy sources. Overall, the contribution made by this thesis promotes greener transportation with fewer associated grid impacts.

Rising fuel prices, depleting fossil fuels, and the long-term benefits of clean energy have all provided the opportunity to comprehensively address the transportation electrification and integration of transportation with electric utilities. Electric vehicles (EVs) have many benefits as compared to conventional gasoline cars. Moreover, electrification of transportation systems would enable increased electricity generation from carbon-free and renewable energy sources, such as wind, solar, and hydro. It is anticipated that the electric utility and transportation systems in the United States will become increasingly integrated and indistinguishable from each other due to the electrification of the transportation system. This panel will consist of researchers coming from academy and industry. The presentations by the panel will give a broad coverage from electric vehicles to integration and impact of electric vehicles to the grid. From vehicle perspective, the panel will focus on typical EV configurations, challenges associated with EV energy management and high performance traction control technology using artificial neural networks. Regarding EV grid integration, the panel will discuss charging management of EVs, EV integration with renewables, and techniques of using a fleet of EVs in support of automatic generation control in a smart grid framework. The panel presentation and discussion should build a foundation for one of the most critical technological areas to enhance U.S. energy security and environmental sustainability.

A structured approach for the design of a model architecture is presented. From a simplified representation of the current situation, the aim is to implement regulations and test solutions in order to reach future climate targets. The challenge is to combine model accuracy to minimise uncertainty of the results on one side, and ease of implementation/plausibility of scenarios on the other side, which often decreases as systems complexify. A stage-wise model expansion is suggested to balance these two criteria. This approach is applied to the case of increased grid integration of electric vehicles (EVs) in Denmark.KeywordsModelling architectureStage-wise approachEV grid integration

The integration of electric vehicles (EVs) will affect both electricity and transport systems and research is needed on finding possible ways to make a smooth transition to the electrification of the road transport. To fully understand the EV integration consequences, the behaviour of the EV drivers and its impact on these two systems should be studied. This paper describes an integrated simulation-based approach, modelling the EV and its interactions in both road transport and electric power systems. The main components of both systems have been considered, and the EV driver behaviour was modelled using a multi-agent simulation platform. Considering a fleet of 1000EV agents, two behavioural profiles were studied (Unaware/Aware) to model EV driver behaviour. The two behavioural profiles represent the EV driver in different stages of EV adoption starting with Unaware EV drivers when the public acceptance of EVs is limited, and developing to Aware EV drivers as the electrification of road transport is promoted in an overall context. The EV agents were modelled to follow a realistic activity-based trip pattern, and the impact of EV driver behaviour was simulated on a road transport and electricity grid. It was found that the EV agents’ behaviour has direct and indirect impact on both the road transport network and the electricity grid, affecting the traffic of the roads, the stress of the distribution network and the utilization of the charging infrastructure.