The penetration of electric vehicles (EVs) in the transportation sector is increasing but conventional internal combustion engine (ICE) based vehicles dominates. To accelerate the adoption of EVs and to achieve sustainable transportation, the bottlenecks need to be elevated that mainly include the high cost EVs, range anxiety, lack of EV charging infrastructure, and the pollution of the grid due to EV chargers. The high cost of EVs is due to costly energy storage systems (ESS) with high energy density. This paper provides a comprehensive review of EV technology that mainly includes electric vehicle supply equipment (EVSE), ESS, and EV chargers. A detailed discussion is presented on the state-of-the-art of EV chargers that include on-/off-board chargers. Different topologies are discussed with low-/high-frequency transformers. The different available power levels for charging are discussed. To reduce the range anxiety the EV chargers based on inductive power transfer (IPT) are discussed. The last part of the paper focuses on the negative impact of EV chargers along with the remedies that can be adopted. The international standards decided by different institutions and adopted universally are discussed in the latter part of this paper and finally, this paper concludes with the near to future advancement in EV technology.

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A Comprehensive Review on Structural Topologies, Power Levels, Energy Storage Systems, and Standards for Electric Vehicle Charging Stations and Their Impacts on Grid

To determine the optimal size of an energy storage system (ESS) in a fast electric vehicle (EV) charging station, minimization of ESS cost, enhancement of EVs’ resilience, and reduction of peak load have been considered in this article. Especially, the resilience aspect of the EVs is focused due to its significance for EVs during power outages. First, the stochastic load of the fast-charging station (FCS) and the resilience load of the EVs are estimated using probability distribution functions. This information is utilized to maintain the energy level in the ESS to ensure the resilience of EVs during power outages. Then, the annualized cost of the ESS is determined using the annual interest rate and lifetime of ESS components. Finally, the optimal ESS size is determined using the annualized ESS cost, penalty cost for buying power during peak hours, and penalty cost for resilience violations. Simulations along with sensitivity analysis of uncertainties (market price, arrival time of EVs, and the residual energy level of EVs), number of EVs in the FCS, and converter ratings are conducted. Simulation results have shown that increasing the penalty cost for peak intervals is a viable solution to decrease the peak load while controlling the cost of the FCS.

Optimal Sizing of Battery Energy Storage System in a Fast EV Charging Station Considering Power Outages

Dynamic protection of power systems with high penetration of renewables: A review of the traveling wave based fault location techniques

This study presents a comprehensive survey on the reliability evaluation of the electrical network system. The impacts of integration of new and renewable energy sources (electric vehicle, energy storage system, solar, and wind) on the reliability of electrical power system (EPS) are discussed. The impacts of these renewable sources have merits/demerits when these sources are integrated with the conventional electric power system. However, the merits are predominant as it includes unlimited, free, and cost-effective resources. The recent researches depict that the uncertainties of renewable energy resources leads to the probabilistic and reliability analyses of EPS. EPS includes offshore and onshore wind farms, micro-grid, energy storage system, and other high voltage grids. It also contains the failure-prone components related to the power systems. For the accomplishment of these aspects, the handling methods of uncertainty parameters in generation, transmission, and distribution systems are discussed. The incorporation of electric vehicles, wind energy system, and energy storage system for reliability assessment is also discussed briefly. This study also presents the scope of a new research area for the researchers on the reliability assessment of renewable energy integrated power system.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-gtd.2019.1402

Reliability enhancement of electrical power system including impacts of renewable energy sources: a comprehensive review

The smart electricity grids have been evolving to a more complex cyber-physical ecosystem of infrastructures with integrated communication networks, new carbon-free sources of power generation, advanced monitoring and control systems, and a myriad of emerging modern physical hardware technologies. With the unprecedented complexity and heterogeneity in dynamic smart grid networks comes additional vulnerability to emerging threats such as cyber attacks. Rapid development and deployment of advanced network monitoring and communication systems on one hand, and the growing interdependence of the electric power grids to a multitude of lifeline critical infrastructures on the other, calls for holistic defense strategies to safeguard the power grids against cyber adversaries. In order to improve the resilience of the power grid against adversarial attacks and cyber intrusions, advancements should be sought on detection techniques, protection plans, and mitigation practices in all electricity generation, transmission, and distribution sectors. This survey discusses such major directions and recent advancements from a lens of different detection techniques, equipment protection plans, and mitigation strategies to enhance the energy delivery infrastructure resilience and operational endurance against cyber attacks. This undertaking is essential since even modest improvements in resilience of the power grid against cyber threats could lead to sizeable monetary savings and an enriched overall social welfare.

/pdf/electric-power-grid-resilience-to-cyber-adversaries-state-of-190drb8ihn.pdf

Electric Power Grid Resilience to Cyber Adversaries: State of the Art

Several safety regulations, particularly concerning the charging of electric vehicles (EVs) are developed to ensure electric safety and prevent hazardous accidents, in which safety requirements for the EV supply equipment (EVSE) and the EV battery are two main driving factors. At present, quantitative assessment of electrical safety considering the operation conditions of large-scale EV charging stations (EVCSs) has still remained a challenge. Driven by the hierarchy of hazard control mechanisms, this article proposes a holistic approach to evaluate the electrical safety of the large-scale EVCSs when coupled to renewable power generation. Our approach mainly focuses on several topics on the operational safety of EVCS primarily concerning: 1) the facility degradation which could potentially result in a compromised EVSE reliability performance and EVCS protection failure; 2) the cyberattack challenges when the smart charging and the communication between EVCSs and electric utilities are enabled; and 3) the potential mismatch between the renewable output and EVCS demand, which could trigger the system stability challenges during normal operation and inability to supply the critical EV loads during outages. The proposed framework will provide informative guidelines to the EVCS operators for continuous monitoring and effective management of the day-to-day EVCS operation.

Electrical Safety Considerations in Large-Scale Electric Vehicle Charging Stations

This paper proposes a two-stage energy management system (EMS) for power grids with massive integration of electric vehicles (EVs) and renewable energy resources. The first stage economic dispatch determines the optimal operating points of charging stations and battery swapping stations (BSS) for EVs under plug-in and battery swapping modes, respectively. The proposed stochastic model predictive control (SMPC) problem in this stage is characterized through a chance-constrained optimization formulation that can effectively capture the system and the forecast uncertainties. A distributed algorithm, the alternating direction method of multipliers (ADMM), is applied to accelerate the optimization computation through parallel computing. The second stage is aimed in coordinating the EV charging mechanisms to continuously follow the first-stage solutions, i.e., the target operating points, and meeting the EV customers’ charging demands captured via the Advanced Metering Infrastructure (AMI). The proposed solution offers a holistic control strategy for large-scale centralized power grids in which the aggregated individual parameters are predictable and the system dynamics do not vary sharply within a short time-interval.

Chance-Constrained Energy Management System for Power Grids With High Proliferation of Renewables and Electric Vehicles

Different electric vehicle (EV) charging algorithms result in different EV charging load profiles, that if aggregated, influence the power grid operation. The existing EV charging demand models are either based on the charging status upon EV arrival or smart charging algorithms reinforced with particular charging methods and/or charging levels. This article proposes a new data-driven approach for EV charging load modeling. We first introduce a mathematical model that characterizes the flexibility of EV charging demand. Advanced simulation procedures are then proposed to identify the parameters of different EV load models and simulate EV charging demand under different electricity market realizations. The proposed EV load modeling approach can simulate different EV operation schedules, charging levels, and customer participation as a benchmark system. The proposed framework will also provide informative guidelines to transmission system operators for EV charging infrastructure planning in modern power systems.

Aggregated Electric Vehicle Load Modeling in Large-Scale Electric Power Systems

Electric distribution utilities are required to continuously deliver reliable electric power to their customers. Regulatory utility commissions often practise reward and penalty schemes to regulate reliability performance of utility companies annually with respect to a desired performance targets. However, the conventional regulation procedures are commonly found based on the customer-based standard reliability indices, which are not able to discern the service characteristics behind the electric meters and, hence, fail to holistically characterise the actual impact of electricity interruption. This study proposes a new method to evaluate the load-based reliability indices in power distribution systems using advanced metering infrastructure data. Furthermore, the authors introduce a reward/penalty regulation scheme for utility regulators to provide a reliability oversight using the proposed load-based reliability metrics. The new load-based reliability metric and the reward/penalty scheme proposed bring about superior advantages as the distribution grids become further complex with a high penetration of distributed energy resources and enabled microgrid flexibilities. Numerical analyses on different settings with and without microgrid considerations reveal the applicability and effectiveness of the proposed approach in real-world scenarios.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-gtd.2017.1809

New reward and penalty scheme for electric distribution utilities employing load-based reliability indices

Geomagnetically induced currents (GICs) in power grids are mainly caused by geomagnetic disturbances especially during solar storms. Such currents can potentially cause negative impacts on power grid equipment and even damage the power transformers resulting in a significant risk of blackouts. Therefore, monitoring GICs in power systems and developing solutions to mitigate their impacts before rising to a certain threatening level is urgently in need. Monitoring GICs is, however, quite a challenge and costly, as they usually appear in forms of DC components in the high voltage transmission lines, which are barely accessible through transformers. By examining the measured currents from the current transformers (CTs), this paper proposes a framework to detect GICs in power transmission systems through a hybrid time-frequency analysis combined with machining learning technology. Simulated results verify that the proposed approach can promisingly estimate GICs in power systems during a variety of grid operating conditions.

Bo Wang

Papers

Electrical Safety Considerations in Large-Scale Electric Vehicle Charging Stations

Chance-Constrained Energy Management System for Power Grids With High Proliferation of Renewables and Electric Vehicles

Aggregated Electric Vehicle Load Modeling in Large-Scale Electric Power Systems

New reward and penalty scheme for electric distribution utilities employing load-based reliability indices

A Machine Learning Approach to Detection of Geomagnetically Induced Currents in Power Grids