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Interactive Integration of Electric Vehicles and Power Networks: Emerging Issues and Solutions

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".

Deadline for manuscript submissions: closed (20 January 2021) | Viewed by 21950

Special Issue Editor


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Guest Editor
Department of Electrical Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Korea

Special Issue Information

Dear Colleagues,

With the increased interest for sustainability, the use of electric vehicles (EVs) has emerged as a popular choice for enabling sustainable energy usage. Operation of EVs not only contribute to decreased dependence on fossil fuel but also address novel issues reported in the modernized power network. Promising results have been reported from various demonstration sites that EVs could be considered as a valuable distribution resource that accelerates flexible and resilient operation of power networks. Meanwhile, EVs would also introduce novel challenges to power grid operation. Installation of EV charging facilities is required and charging demand of EVs should be effectively addressed for stable power system operation.

 This special issue attempts to discuss issues and solutions related to challenges and opportunities introduced by EVs. Topics of interest include, but are not limited to:

*. Approaches for prediction of EV charging demand and renewable energy resource output

*. Approaches for distributing method of EV charging demand

*. Effect of EV charging to power system operation (e.g., stability, control, reliability) and infrastructure

*. EV charging demand and transmission & distribution network

*. EV scheduling and Demand Response

*. EV smart charging method(V1G) and Vehicle-to-Grid(V2G)

*. Case study results on EV integration from actual demonstration sites

Prof. Dr. Sungwoo Bae
Guest Editor

Manuscript Submission Information

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Keywords

  • Electric vehicle charging demand prediction
  • Electric vehicle charging demand distribution
  • Renewable energy resource output forecast for EV charging infrastructure
  • Machine learning
  • Deep learning
  • Power system
  • Distribution network
  • Transmission network
  • Power system infrastructure
  • Energy market
  • V1G (Smart Charging)
  • V2G (Vehicle to Grid)
  • G2V (Grid to Vehicle)

Published Papers (7 papers)

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Research

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14 pages, 3605 KiB  
Article
Analysis of Daily Load Patterns Taking into Consideration PEVs Charging Stations in Seoul, South Korea
by Sangbong Choi, Changsoo Kim and Backsub Sung
Energies 2021, 14(9), 2662; https://doi.org/10.3390/en14092662 - 6 May 2021
Cited by 1 | Viewed by 1595
Abstract
This paper presents a methodology to calculate daily charging load curves in Seoul, South Korea, by taking into account plug-in electric vehicles (PEVs) charging stations, allowing Seoul’s government to determine the PEVs charging effect on the load. In particular, the study calculates the [...] Read more.
This paper presents a methodology to calculate daily charging load curves in Seoul, South Korea, by taking into account plug-in electric vehicles (PEVs) charging stations, allowing Seoul’s government to determine the PEVs charging effect on the load. In particular, the study calculates the charging power of uncontrolled PEVs charging in terms of the daily operating characteristics of a vehicle traveling between home and workplace, with respect to PEVs charging stations in the city, according to the PEVs’ market share. For the controlled PEVs charging strategy based on morning and afternoon work-to-home and vice versa traffic characteristics and time-of-use (TOU) prices in Seoul, the study calculates daily load patterns of uncontrolled and controlled charging scenarios. After adding the calculated values to the existing load, the study assesses and compares their effects on the power grid. The results are as follows. If by 2030 the share of electric vehicles is 10%, compared to the existing load, the total load increases by about 13% between 9:00 and 11:00 in the morning for the uncontrolled mode and by about 10% for the controlled mode. The total load increases by about 16% between 20:00 and 22:00 for the uncontrolled mode and 17% for the controlled mode. However, if by 2040 the share of electric vehicles is 30%, compared to the existing load, the total load increases by about 35% between 9:00 and 11:00 in the morning for the uncontrolled mode and by about 32% for the controlled mode. Between 20:00 and 22:00, the uncontrolled mode’s total charging load increases by about 35% and the controlled mode’s total load by about 32%. The analysis also demonstrated that it was possible to achieve a significant load-leveling effect in all charging periods for the controlled mode, with the daily load pattern’s average leveling rate increasing by 8% and 13% in 2030 and 2040, respectively, based on the TOU price system compared with the uncontrolled mode. Based on these results, it is possible to determine the PEVs’ hourly charging load effect on the power grid in Seoul and establish a PEVs charging load management plan to prevent the power grid reinforcement and expansion and to satisfy its overload constraint by using an appropriate TOU price plan. Full article
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16 pages, 1252 KiB  
Article
Uncontrolled Electric Vehicle Charging Impacts on Distribution Electric Power Systems with Primarily Residential, Commercial or Industrial Loads
by C. Birk Jones, Matthew Lave, William Vining and Brooke Marshall Garcia
Energies 2021, 14(6), 1688; https://doi.org/10.3390/en14061688 - 18 Mar 2021
Cited by 32 | Viewed by 3445
Abstract
An increase in Electric Vehicles (EV) will result in higher demands on the distribution electric power systems (EPS) which may result in thermal line overloading and low voltage violations. To understand the impact, this work simulates two EV charging scenarios (home- and work-dominant) [...] Read more.
An increase in Electric Vehicles (EV) will result in higher demands on the distribution electric power systems (EPS) which may result in thermal line overloading and low voltage violations. To understand the impact, this work simulates two EV charging scenarios (home- and work-dominant) under potential 2030 EV adoption levels on 10 actual distribution feeders that support residential, commercial, and industrial loads. The simulations include actual driving patterns of existing (non-EV) vehicles taken from global positioning system (GPS) data. The GPS driving behaviors, which explain the spatial and temporal EV charging demands, provide information on each vehicles travel distance, dwell locations, and dwell durations. Then, the EPS simulations incorporate the EV charging demands to calculate the power flow across the feeder. Simulation results show that voltage impacts are modest (less than 0.01 p.u.), likely due to robust feeder designs and the models only represent the high-voltage (“primary”) system components. Line loading impacts are more noticeable, with a maximum increase of about 15%. Additionally, the feeder peak load times experience a slight shift for residential and mixed feeders (≈1 h), not at all for the industrial, and 8 h for the commercial feeder. Full article
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13 pages, 2534 KiB  
Article
A Probabilistic Modeling Based on Monte Carlo Simulation of Wind Powered EV Charging Stations for Steady-States Security Analysis
by Sunoh Kim and Jin Hur
Energies 2020, 13(20), 5260; https://doi.org/10.3390/en13205260 - 10 Oct 2020
Cited by 23 | Viewed by 2529
Abstract
As renewable energy resources such as wind and solar power are developing and the penetration of electric vehicles (EVs) is increasingly integrated into existing systems, uncertainty and variability in power systems have become important issues. The charging demands for EVs and wind power [...] Read more.
As renewable energy resources such as wind and solar power are developing and the penetration of electric vehicles (EVs) is increasingly integrated into existing systems, uncertainty and variability in power systems have become important issues. The charging demands for EVs and wind power output are recognized as highly variable generation resources (VGRs) with uncertainty, which can cause unexpected disturbances such as short circuits. This can deteriorate the reliability of existing power systems. In response, research is required to identify the uncertainties presented by VGRs and is required to examine the ability of power system models to reflect those uncertainties. The deterministic method, which is the most basic method that is currently in use, does not reflect the uncertainty of system components. Therefore, this paper proposes a probabilistic method to assess the steady-state security of power systems, reflecting the uncertainty of VGRs using Monte Carlo simulation (MCS). In the proposed method, the empirical EVs charging demand and wind power output data are modeled as a probability distribution, and then MCS is performed, integrating the power system operation to represent the steady-state security as a probability index. To verify the method proposed in this paper, a security analysis was performed based on the systems in Jeju Island, South Korea, where the penetration of wind power and EVs is expanding rapidly. Full article
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19 pages, 2560 KiB  
Article
V2G Strategy for Improvement of Distribution Network Reliability Considering Time Space Network of EVs
by Hak-Ju Lee, Byeong-Chan Oh, Seok-Woong Kim and Sung-Yul Kim
Energies 2020, 13(17), 4415; https://doi.org/10.3390/en13174415 - 26 Aug 2020
Cited by 3 | Viewed by 2017
Abstract
Reliability is an important index which determines the power service and quality provided to customers. As the demand increases continuously and the system changes in accordance with the environmental regulation, the reliability assessment in the distribution system becomes crucial. In this paper, we [...] Read more.
Reliability is an important index which determines the power service and quality provided to customers. As the demand increases continuously and the system changes in accordance with the environmental regulation, the reliability assessment in the distribution system becomes crucial. In this paper, we propose methods for improving the reliability of the distribution system using electric vehicles (EVs) in the system. In this paper, EVs are used as power supplying devices, such as a transportable energy storage system (ESS) which supplies power when fault occurs in the system, and by using a time–space network (TSN) in particular, EV capacity in accordance with the load arrival time was calculated. Unlike other existing reliability assessments, we did not use the average load of customers. Instead, by taking into account the load pattern by times, we considered the priority for load supply in accordance with the failure scenarios and failure times. Based on the priority calculated for each time of failure and failure scenario, plans for EV operation to minimize expected customer interruption cost (ECOST), the reliability index in the distribution system, were established. Finally, a case study was performed using the IEEE RBTS (Roy Billinton Test System) 2 Bus and the performance of the model proposed in this paper was verified based on the result. Full article
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13 pages, 8806 KiB  
Article
Modeling the Impact of Electric Vehicle Charging Systems on Electric Power Quality
by Joanna Baraniak and Jacek Starzyński
Energies 2020, 13(15), 3951; https://doi.org/10.3390/en13153951 - 1 Aug 2020
Cited by 18 | Viewed by 3201
Abstract
Recently, there has been dynamic development of electromobility. This trend is predicted to grow exponentially, which will contribute to the creation of an extensive infrastructure of electric car charging points. For distribution network operators, this implies that in addition to the increase in [...] Read more.
Recently, there has been dynamic development of electromobility. This trend is predicted to grow exponentially, which will contribute to the creation of an extensive infrastructure of electric car charging points. For distribution network operators, this implies that in addition to the increase in demand for power and electricity, the number of converter systems connected to their networks will also increase. It is therefore necessary to determine the potential impact of electric vehicle charging systems on electricity quality. To this end, the authors of the present study developed simulation models based on measurements of the actual charger and the data provided by the manufacturers of the equipment and using simulation models widely described in the literature. On the basis of the study results, the impact of electric car chargers on electric power quality was assessed, and attention was given to the opportunities offered by the development of charging systems with vehicle-to-grid (V2G) functionality. Changes in technical standards aimed at selecting power supply cables by considering their heating under the influence of higher current harmonics generated by converter systems were proposed. Full article
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23 pages, 7691 KiB  
Article
Assessment and Mitigation of Electric Vehicle Charging Demand Impact to Transformer Aging for an Apartment Complex
by Shin-Ki Hong, Sung Gu Lee and Myungchin Kim
Energies 2020, 13(10), 2571; https://doi.org/10.3390/en13102571 - 19 May 2020
Cited by 9 | Viewed by 2977
Abstract
Due to the increasing use of Electric Vehicles (EVs), the effect of the EV charging power demand on the reliability of the power system infrastructure needs to be addressed. In apartment complexes, which have emerged as a common residential type in metropolitan areas [...] Read more.
Due to the increasing use of Electric Vehicles (EVs), the effect of the EV charging power demand on the reliability of the power system infrastructure needs to be addressed. In apartment complexes, which have emerged as a common residential type in metropolitan areas and highly populated districts, high charging demand could result in substantial stress to distribution networks. In this work, the effect of EV charging power demand in an apartment complex on the aging of the Distribution Transformer (DT) is studied. A methodology based on the stochastic characterization of vehicle usage profiles and user charging patterns is developed to obtain realistic EV charging demand profiles. Based on the modeled EV charging profile and the transformer thermal model, the effect of different EV penetration ratios on DT aging for an apartment complex in the Republic of Korea is studied. Results for an EV penetration ratio of up to 30% indicated that DT aging could be accelerated by up to 40%, compared to the case without EV charging. To mitigate this accelerated DT aging caused by EV charging, the effectiveness of two integration approaches of Photovoltaic (PV) sources was studied. Based on a case study that included a realistic PV generation profile, it was demonstrated that a significant contribution to DT reliability could be achieved via the operation of PV sources. A more apparent contribution of PV integration was observed with an energy storage installation at higher EV penetration ratios. At an EV penetration ratio of 30%, a maximum decrease of 41.8% in the loss-of-life probability of the DT was achieved. The effects of different PV integration approaches and power management details on DT aging were also studied. The results demonstrate that the EV charging demand could introduce a significant level of stress to DTs and that this impact can be effectively mitigated by installing PV sources. These observations are expected to contribute toward the effective planning of power system infrastructures that support the design of sustainable cities with the widespread use of EVs. Full article
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Review

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24 pages, 3122 KiB  
Review
Electrical Vehicle Charging Services Planning and Operation with Interdependent Power Networks and Transportation Networks: A Review of the Current Scenario and Future Trends
by Shafqat Jawad and Junyong Liu
Energies 2020, 13(13), 3371; https://doi.org/10.3390/en13133371 - 1 Jul 2020
Cited by 21 | Viewed by 5092
Abstract
The growing trend in electrical vehicle (EV) deployment has transformed independent power network and transportation network studies into highly congested interdependent network performance evaluations assessing their impact on power and transportation systems. Electrified transportation is highly capable of intensifying the interdependent correlations across [...] Read more.
The growing trend in electrical vehicle (EV) deployment has transformed independent power network and transportation network studies into highly congested interdependent network performance evaluations assessing their impact on power and transportation systems. Electrified transportation is highly capable of intensifying the interdependent correlations across charging service, transportation, and power networks. However, the evaluation of the complex coupled relationship across charging services, transportation, and power networks poses several challenges, including an impact on charging scheduling, traffic congestion, charging loads on the power grid, and high costs. Therefore, this article presents comparative survey analytics of large-scale EV integration’s impact on charging service network scheduling, transportation networks, and power networks. Moreover, price mechanism strategies to determine the charging fares, minimize investment profits, diminish traffic congestion, and reduce power distribution constraints under the influence of various factors were carried out. Additionally, the survey analysis stipulates the interdependent network performance index, ascertaining travel distance, route selection, long-term and short-term planning, and different infrastructure strategies. Finally, the limitations of the proposed study, potential research trends, and critical technologies are demonstrated for future inquiries. Full article
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