Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (258)

Search Parameters:
Keywords = fast charging station

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
25 pages, 2661 KiB  
Article
Fuzzy Logic-Based Energy Management Strategy for Hybrid Renewable System with Dual Storage Dedicated to Railway Application
by Ismail Hacini, Sofia Lalouni Belaid, Kassa Idjdarene, Hammoudi Abderazek and Kahina Berabez
Technologies 2025, 13(8), 334; https://doi.org/10.3390/technologies13080334 - 1 Aug 2025
Viewed by 204
Abstract
Railway systems occupy a predominant role in urban transport, providing efficient, high-capacity mobility. Progress in rail transport allows fast traveling, whilst environmental concerns and CO2 emissions are on the rise. The integration of railway systems with renewable energy source (RES)-based stations presents [...] Read more.
Railway systems occupy a predominant role in urban transport, providing efficient, high-capacity mobility. Progress in rail transport allows fast traveling, whilst environmental concerns and CO2 emissions are on the rise. The integration of railway systems with renewable energy source (RES)-based stations presents a promising avenue to improve the sustainability, reliability, and efficiency of urban transport networks. A storage system is needed to both ensure a continuous power supply and meet train demand at the station. Batteries (BTs) offer high energy density, while supercapacitors (SCs) offer both a large number of charge and discharge cycles, and high-power density. This paper proposes a hybrid RES (photovoltaic and wind), combined with batteries and supercapacitors constituting the hybrid energy storage system (HESS). One major drawback of trains is the long charging time required in stations, so they have been fitted with SCs to allow them to charge up quickly. A new fuzzy energy management strategy (F-EMS) is proposed. This supervision strategy optimizes the power flow between renewable energy sources, HESS, and trains. DC bus voltage regulation is involved, maintaining BT and SC charging levels within acceptable ranges. The simulation results, carried out using MATLAB/Simulink, demonstrate the effectiveness of the suggested fuzzy energy management strategy for various production conditions and train demand. Full article
Show Figures

Figure 1

25 pages, 9888 KiB  
Article
An Optimal Multi-Zone Fast-Charging System Architecture for MW-Scale EV Charging Sites
by Sai Bhargava Althurthi and Kaushik Rajashekara
World Electr. Veh. J. 2025, 16(7), 389; https://doi.org/10.3390/wevj16070389 - 10 Jul 2025
Viewed by 270
Abstract
In this paper, a detailed review of electric vehicle (EV) charging station architectures is first presented, and then an optimal architecture suitable for a large MW-scale EV fast-charging station (EVFS) with multiple fast chargers is proposed and evaluated. The study examines various EVFS [...] Read more.
In this paper, a detailed review of electric vehicle (EV) charging station architectures is first presented, and then an optimal architecture suitable for a large MW-scale EV fast-charging station (EVFS) with multiple fast chargers is proposed and evaluated. The study examines various EVFS architectures, including those currently deployed in commercial sites. Most EVFS implementations use either a common AC-bus or a common DC-bus configuration, with DC-bus architectures being slightly more predominant. The paper analyzes the EV charging and battery energy storage system (BESS) requirements for future large-scale EVFSs and identifies key implementation challenges associated with the full adoption of the common DC-bus approach. To overcome these limitations, a novel multi-zone EVFS architecture is proposed that employs an optimal combination of isolated and non-isolated DC-DC converter topologies while maintaining galvanic isolation for EVs. The system efficiency and total power converter capacity requirements of the proposed architecture are evaluated and compared with those of other EVFS models. A major feature of the proposed design is its multi-zone division and zonal isolation capabilities, which are not present in conventional EVFS architectures. These advantages are demonstrated through a scaled-up model consisting of 156 EV fast chargers. The analysis highlights the superior performance of the proposed multi-zone EVFS architecture in terms of efficiency, total power converter requirements, fault tolerance, and reduced grid impacts, making it the best solution for reliable and scalable MW-scale commercial EVFS systems of the future. Full article
Show Figures

Figure 1

21 pages, 2201 KiB  
Article
Evaluating China’s Electric Vehicle Adoption with PESTLE: Stakeholder Perspectives on Sustainability and Adoption Barriers
by Daniyal Irfan and Xuan Tang
Sustainability 2025, 17(14), 6258; https://doi.org/10.3390/su17146258 - 8 Jul 2025
Viewed by 528
Abstract
The electric vehicle (EV) business model integrates advanced battery technology, dynamic power train architectures, and intelligent energy management systems with ecosystem strategies and digital services. It incorporates environmental sustainability through lifecycle analysis and renewable energy integration. China, with 9.49 million EV sales in [...] Read more.
The electric vehicle (EV) business model integrates advanced battery technology, dynamic power train architectures, and intelligent energy management systems with ecosystem strategies and digital services. It incorporates environmental sustainability through lifecycle analysis and renewable energy integration. China, with 9.49 million EV sales in 2023 (33% market share), faces infrastructure gaps constraining further growth. China is strategically mitigating CO2 emissions while fostering economic expansion, notwithstanding constraints such as suboptimal battery technology advancements, elevated production expenditure, and enduring ecological impacts. This Political, Economic, Social, Technological, Legal, Environmental (PESTLE) assessment, operationalized through a survey of 800 stakeholders and Statistical Package for the Social Sciences IBM SPSS SPSS (Version 28) quantitative analysis (factor loading = 0.73 for Technology; eigenvalue = 4.12), identifies infrastructure gaps as the dominant barrier (72% of stakeholders). Political factors (β = 0.82) emerged as the strongest adoption predictor, outweighing economic subsidies in significance. The adoption of EVs in China presents a significant prospect for reducing CO2 emissions and advancing technology. However, economic barriers, market dynamics, inadequate infrastructure, regulatory uncertainty, and social acceptance issues are addressed in the assessment. The study recommends prioritizing infrastructure investment (e.g., 500 K fast-charging stations by 2027) and policy stability to overcome adoption barriers. This study provides three key advances: (1) quantification of PESTLE factor weights via factor analysis, revealing technological (infrastructure) and political factors as dominant; (2) identification of infrastructure gaps, not subsidies, as the primary adoption barrier; and (3) demonstration of infrastructure’s persistence post-subsidy cuts. These insights redefine EV adoption priorities in China. Full article
Show Figures

Figure 1

19 pages, 3238 KiB  
Article
Optimal Location for Electric Vehicle Fast Charging Station as a Dynamic Load for Frequency Control Using Particle Swarm Optimization Method
by Yassir A. Alhazmi and Ibrahim A. Altarjami
World Electr. Veh. J. 2025, 16(7), 354; https://doi.org/10.3390/wevj16070354 - 25 Jun 2025
Viewed by 363
Abstract
There are significant emissions of greenhouse gases into the atmosphere from the transportation industry. As a result, the idea that electric vehicles (EVs) offer a revolutionary way to reduce greenhouse gas emissions and our reliance on rapidly depleting petroleum supplies has been put [...] Read more.
There are significant emissions of greenhouse gases into the atmosphere from the transportation industry. As a result, the idea that electric vehicles (EVs) offer a revolutionary way to reduce greenhouse gas emissions and our reliance on rapidly depleting petroleum supplies has been put forward. EVs are becoming more common in many nations worldwide, and the rapid uptake of this technology is heavily reliant on the growth of charging stations. This is leading to a significant increase in their number on the road. This rise has created an opportunity for EVs to be integrated with the power system as a Demand Response (DR) resource in the form of an EV fast charging station (EVFCS). To allocate electric vehicle fast charging stations as a dynamic load for frequency control and on specific buses, this study included the optimal location for the EVFCS and the best controller selection to obtain the best outcomes as DR for various network disruptions. The optimal location for the EVFCS is determined by applying transient voltage drop and frequency nadir parameters to the Particle Swarm Optimization (PSO) location model as the first stage of this study. The second stage is to explore the optimal regulation of the dynamic EVFCS load using the PSO approach for the PID controller. PID controller settings are acquired to efficiently support power system stability in the event of disruptions. The suggested model addresses various types of system disturbances—generation reduction, load reduction, and line faults—when it comes to the Kundur Power System and the IEEE 39 bus system. The results show that Bus 1 then Bus 4 of the Kundur System and Bus 39 then Bus 1 in the IEEE 39 bus system are the best locations for dynamic EVFCS. Full article
Show Figures

Figure 1

47 pages, 5201 KiB  
Article
Mitigation of Voltage Magnitude Profiles Under High-Penetration-Level Fast-Charging Stations Using Optimal Capacitor Placement Integrated with Renewable Energy Resources in Unbalanced Distribution Networks
by Pongsuk Pilalum, Radomboon Taksana, Noppanut Chitgreeyan, Wutthichai Sa-nga-ngam, Supapradit Marsong, Krittidet Buayai, Kaan Kerdchuen, Yuttana Kongjeen and Krischonme Bhumkittipich
Smart Cities 2025, 8(4), 102; https://doi.org/10.3390/smartcities8040102 - 23 Jun 2025
Viewed by 547
Abstract
The rapid adoption of electric vehicles (EVs) and the increasing use of photovoltaic (PV) generation have introduced new operational challenges for unbalanced power distribution systems. These include elevated power losses, voltage imbalances, and adverse environmental impacts. This study proposed a hybrid objective optimization [...] Read more.
The rapid adoption of electric vehicles (EVs) and the increasing use of photovoltaic (PV) generation have introduced new operational challenges for unbalanced power distribution systems. These include elevated power losses, voltage imbalances, and adverse environmental impacts. This study proposed a hybrid objective optimization framework to address these issues by minimizing real and reactive power losses, voltage deviations, voltage imbalance indexes, and CO2 emissions. Nineteen simulation cases were analyzed under various configurations incorporating EV integration, PV deployment, reactive power compensation, and zonal control strategies. An improved gray wolf optimizer (IGWO) was employed to determine optimal placements and control settings. Among all cases, Case 16 yielded the lowest objective function value, representing the most effective trade-off between technical performance, voltage stability, and sustainability. The optimized configuration significantly improved the voltage balance, reduced system losses, and maintained the average voltage within acceptable limits. Additionally, all optimized scenarios achieved meaningful reductions in CO2 emissions compared to the base case. The results were validated with an objective function Fbest as a reliable composite performance index and demonstrated the effectiveness of coordinated zone-based optimization. This approach provides practical insights for future smart grid planning under dynamic, renewable, rich, and EV-dominated operating conditions. Full article
(This article belongs to the Topic Smart Energy Systems, 2nd Edition)
Show Figures

Figure 1

35 pages, 8378 KiB  
Review
A Comprehensive Review of Partial Power Converter Topologies and Control Methods for Fast Electric Vehicle Charging Applications
by Babar Ejaz, Ramon Zamora, Carlos Reusser and Xin Lin
Electronics 2025, 14(10), 1928; https://doi.org/10.3390/electronics14101928 - 9 May 2025
Cited by 1 | Viewed by 1440
Abstract
This paper provides a comprehensive review of Partial Power Converter (PPC) topologies and control methods for fast electric vehicle (EV) charging applications. Partial Power Converters are gaining traction to enhance converter efficiency, reduce power losses, and minimize component sizes by processing only a [...] Read more.
This paper provides a comprehensive review of Partial Power Converter (PPC) topologies and control methods for fast electric vehicle (EV) charging applications. Partial Power Converters are gaining traction to enhance converter efficiency, reduce power losses, and minimize component sizes by processing only a portion of the total power. This review covers key PPC topologies, including different partial power converters, and highlights their advantages and limitations in the context of EV charging. Various control methods that optimize the performance of these converters are also discussed. The paper presents a comparative analysis between partial power and full power converters. Finally, this review synthesizes the main findings and proposes guidelines for selecting appropriate PPC architectures for future fast EV charging stations. Full article
Show Figures

Figure 1

31 pages, 7481 KiB  
Article
A Multi-Scheme Comparison Framework for Ultra-Fast Charging Stations with Active Load Management and Energy Storage Under Grid Capacity Constraints
by Qingyu Yin, Lili Li, Jian Zhang, Xiaonan Liu and Boqiang Ren
World Electr. Veh. J. 2025, 16(5), 250; https://doi.org/10.3390/wevj16050250 - 27 Apr 2025
Viewed by 570
Abstract
Grid capacity constraints present a prominent challenge in the construction of ultra-fast charging (UFC) stations. Active load management (ALM) and battery energy storage systems (BESSs) are currently two primary countermeasures to address this issue. ALM allows UFC stations to install larger-capacity transformers by [...] Read more.
Grid capacity constraints present a prominent challenge in the construction of ultra-fast charging (UFC) stations. Active load management (ALM) and battery energy storage systems (BESSs) are currently two primary countermeasures to address this issue. ALM allows UFC stations to install larger-capacity transformers by utilizing valley capacity margins to meet the peak charging demand during grid valley periods, while BESSs rely more on energy storage batteries to solve the gap between the transformer capacity and charging demand This paper proposes a four-quadrant classification method and defines four types of schemes for UFC stations to address grid capacity constraints: (1) ALM with a minimal BESS (ALM-Smin), (2) ALM with a maximal BESS (ALM-Smax), (3) passive load management (PLM) with a minimal BESS (PLM-Smin), and (4) PLM with a maximal BESS (PLM-Smax). A generalized comparison framework is established as follows: First, daily charging load profiles are simulated based on preset vehicle demand and predefined charger specifications. Next, transformer capacity, BESS capacity, and daily operational profiles are calculated for each scheme. Finally, a comprehensive economic evaluation is performed using the levelized cost of electricity (LCOE) and internal rate of return (IRR). A case study of a typical public UFC station in Tianjin, China, validates the effectiveness of the proposed schemes and comparison framework. A sensitivity analysis explored how grid interconnection costs and BESS costs influence decision boundaries between schemes. The study concludes by highlighting its contributions, limitations, and future research directions. Full article
(This article belongs to the Special Issue Fast-Charging Station for Electric Vehicles: Challenges and Issues)
Show Figures

Figure 1

26 pages, 3460 KiB  
Article
Clean Energy Self-Consistent Systems for Automated Guided Vehicle (AGV) Logistics Scheduling in Automated Ports
by Jie Wang, Yuqiang Li, Zhiqiang Liu and Minmin Yuan
Sustainability 2025, 17(8), 3411; https://doi.org/10.3390/su17083411 - 11 Apr 2025
Viewed by 979
Abstract
To enhance the logistics scheduling efficiency of automated guided vehicles (AGVs) in automated ports and achieve the orderly charging and battery swapping of AGVs as well as self-sufficient clean energy, this paper proposes an integrated optimization method. The method first utilizes graph theory [...] Read more.
To enhance the logistics scheduling efficiency of automated guided vehicles (AGVs) in automated ports and achieve the orderly charging and battery swapping of AGVs as well as self-sufficient clean energy, this paper proposes an integrated optimization method. The method first utilizes graph theory to construct a theoretical model that includes AGVs, the port road network, and charging and battery-swapping stations, in order to analyze the optimal logistics scheduling and charging and swapping strategies. Subsequently, for the multi-objective optimization problems in AGV logistics scheduling and charging and swapping, a fast solution method based on the immune optimization algorithm is proposed, with scheduling time and the self-sufficiency rate of clean energy for port AGVs as the constraint conditions. Finally, the effectiveness of the proposed model and algorithm is verified through a simulation scenario. The results show that in the simulated port logistics scenario, after optimization, the total operation time of AGVs is significantly reduced. Compared with the cases that only consider scheduling time, the charging strategy, or wind and solar output, the average clean energy self-sufficiency rate under the proposed strategy increased by 82.7%, 27.5%, and 53.9%, respectively. In addition, as the weight of the self-sufficiency rate increases, both the total driving time and the total clean energy self-sufficiency rate of AGVs show an upward trend and are approximately linearly related. Within the specified maximum scheduling time, the actual scheduling time and self-sufficiency rate can be flexibly coordinated, with significant carbon reduction benefits. Full article
Show Figures

Figure 1

25 pages, 2619 KiB  
Article
Research on the Location and Capacity Determination Strategy of Off-Grid Wind–Solar Storage Charging Stations Based on Path Demand
by Guangyuan Zhu, Weiqing Wang and Wei Zhu
Processes 2025, 13(3), 786; https://doi.org/10.3390/pr13030786 - 8 Mar 2025
Cited by 1 | Viewed by 820
Abstract
To address the challenges of cross-city travel for different types of electric vehicles (EV) and to tackle the issue of rapid charging in regions with weak power grids, this paper presents a strategic approach for locating and sizing highway charging stations tailored to [...] Read more.
To address the challenges of cross-city travel for different types of electric vehicles (EV) and to tackle the issue of rapid charging in regions with weak power grids, this paper presents a strategic approach for locating and sizing highway charging stations tailored to such grid limitations. Initially, considering the initial EV state of charge, a path-demand-based model for EV charging station location–allocation is proposed to optimize station numbers and enhance vehicle flow, which indicates the passing rate of vehicles. Subsequently, a capacity configuration model is formulated, integrating wind, photovoltaic, storage, and diesel generators to manage the stations’ load. This model introduces a new objective function, the annual comprehensive cost, encompassing installation, operation, maintenance, wind and solar curtailment, and diesel generation costs. Simulation examples on north-western cross-city highways validate the efficacy of this approach, showing that the proposed wind–solar storage fast-charging station site selection and capacity optimization model can effectively cater to diverse electric vehicle charging demands. Moreover, it achieves a 90% self-consistency rate during operation across various typical daily scenarios, ensuring a secure and economically viable operational performance. Full article
(This article belongs to the Section Energy Systems)
Show Figures

Figure 1

24 pages, 399 KiB  
Review
Intelligent Monitoring Systems for Electric Vehicle Charging
by Jaime A. Martins and João M. F. Rodrigues
Appl. Sci. 2025, 15(5), 2741; https://doi.org/10.3390/app15052741 - 4 Mar 2025
Cited by 1 | Viewed by 3310
Abstract
The growing adoption of electric vehicles (EVs) presents new challenges for managing parking infrastructure, particularly concerning charging station utilization and user behavior patterns. This review examines the current state-of-the-art in intelligent monitoring systems for EV charging stations in parking facilities. We specifically focus [...] Read more.
The growing adoption of electric vehicles (EVs) presents new challenges for managing parking infrastructure, particularly concerning charging station utilization and user behavior patterns. This review examines the current state-of-the-art in intelligent monitoring systems for EV charging stations in parking facilities. We specifically focus on two key inefficiencies: vehicles occupying charging spots beyond the optimal fast-charging range (80% state-of-charge) and remaining connected even after reaching full capacity (100%). We analyze the theoretical and practical foundations of these systems, summarizing existing research on intelligent monitoring architectures and commercial implementations. Building on this analysis, we also propose a novel monitoring framework that integrates Internet of things (IoT) sensors, edge computing, and cloud services to enable real-time monitoring, predictive maintenance, and adaptive control. This framework addresses both the technical aspects of monitoring systems and the behavioral factors influencing charging station management. Based on a comparative analysis and simulation studies, we propose performance benchmarks and outline critical research directions requiring further experimental validation. The proposed architecture aims to offer a scalable, adaptable, and secure solution for optimizing EV charging infrastructure utilization while addressing key research gaps in the field. Full article
(This article belongs to the Special Issue Feature Review Papers in "Computing and Artificial Intelligence")
Show Figures

Figure 1

34 pages, 4254 KiB  
Article
Optimized Strategy for Energy Management in an EV Fast Charging Microgrid Considering Storage Degradation
by Joelson Lopes da Paixão, Alzenira da Rosa Abaide, Gabriel Henrique Danielsson, Jordan Passinato Sausen, Leonardo Nogueira Fontoura da Silva and Nelson Knak Neto
Energies 2025, 18(5), 1060; https://doi.org/10.3390/en18051060 - 21 Feb 2025
Cited by 1 | Viewed by 773
Abstract
Current environmental challenges demand immediate action, especially in the transport sector, which is one of the largest CO2 emitters. Vehicle electrification is considered an essential strategy for emission mitigation and combating global warming. This study presents methodologies for the modeling and energy [...] Read more.
Current environmental challenges demand immediate action, especially in the transport sector, which is one of the largest CO2 emitters. Vehicle electrification is considered an essential strategy for emission mitigation and combating global warming. This study presents methodologies for the modeling and energy management of microgrids (MGs) designed as charging stations for electric vehicles (EVs). Algorithms were developed to estimate daily energy generation and charging events in the MG. These data feed an energy management algorithm aimed at minimizing the costs associated with energy trading operations, as well as the charging and discharging cycles of the battery energy storage system (BESS). The problem constraints ensure the safe operation of the system, availability of backup energy for off-grid conditions, preference for reduced tariffs, and optimized management of the BESS charge and discharge rates, considering battery wear. The grid-connected MG used in our case study consists of a wind turbine (WT), photovoltaic system (PVS), BESS, and an electric vehicle fast charging station (EVFCS). Located on a highway, the MG was designed to provide fast charging, extending the range of EVs and reducing drivers’ range anxiety. The results of this study demonstrated the effectiveness of the proposed energy management approach, with the optimization algorithm efficiently managing energy flows within the MG while prioritizing lower operational costs. The inclusion of the battery wear model makes the optimizer more selective in terms of battery usage, operating it in cycles that minimize BESS wear and effectively prolong its lifespan. Full article
(This article belongs to the Section E: Electric Vehicles)
Show Figures

Figure 1

17 pages, 526 KiB  
Article
On-Road Wireless EV Charging Systems as a Complementary to Fast Charging Stations in Smart Grids
by Fawzi Alorifi, Walied Alfraidi and Mohamed Shalaby
World Electr. Veh. J. 2025, 16(2), 99; https://doi.org/10.3390/wevj16020099 - 12 Feb 2025
Cited by 2 | Viewed by 2816
Abstract
Electric vehicle (EV) users have the flexibility to fulfill their charging needs using either high-speed charging stations or innovative on-road wireless charging systems, ensuring uninterrupted travel to their destinations. These options present a spectrum of benefits, enhancing convenience and efficiency. The adoption of [...] Read more.
Electric vehicle (EV) users have the flexibility to fulfill their charging needs using either high-speed charging stations or innovative on-road wireless charging systems, ensuring uninterrupted travel to their destinations. These options present a spectrum of benefits, enhancing convenience and efficiency. The adoption of on-road wireless charging as a complementary method influences both the timing and extent of demand at fast-charging stations. This study introduces a comprehensive probabilistic framework to analyze EV arrival rates at fast-charging facilities, incorporating the impact of on-road wireless charging availability. The proposed model utilizes transportation data, including patterns from the US National Household Travel Survey (NHTS), to predict the specific times when EVs would need fast charging. To account for uncertainties in EV user decisions concerning charging preferences, a Monte Carlo simulation (MCS) approach is employed, ensuring a comprehensive analysis of charging behaviors and their potential impact on charging stations. A queuing model is developed to estimate the charging demand for numerous electric vehicles at a charging station, considering both scenarios: on-road EV wireless charging and relying exclusively on fast-charging stations. This study includes an analysis of a case and its simulation results based on a 32-bus distribution system and data from the US National Household Travel Survey (NHTS). The results indicate that integrating on-road EV wireless charging as complementary to fast charging significantly reduces the peak load at the charging station. Additionally, considering the on-road EV wireless charging system, the peak load of the station no longer aligns with the peak load of the power grid, resulting in improved power system capacity and deferred system upgrades. Full article
(This article belongs to the Special Issue Fast-Charging Station for Electric Vehicles: Challenges and Issues)
Show Figures

Figure 1

24 pages, 9516 KiB  
Article
Review on Noise Generation Issues and Noise Mitigation Methods in Electric Vehicle Charging Systems
by Marcin Jarnut, Jacek Kaniewski and Mariusz Buciakowski
Energies 2025, 18(4), 778; https://doi.org/10.3390/en18040778 - 7 Feb 2025
Cited by 1 | Viewed by 1218
Abstract
This paper presents an overview of issues related to noise generation in electric vehicle (EV) charging systems. It discusses the requirements for noise reduction in locations where charging stations are most commonly installed. The primary sources of noise in EV charging stations are [...] Read more.
This paper presents an overview of issues related to noise generation in electric vehicle (EV) charging systems. It discusses the requirements for noise reduction in locations where charging stations are most commonly installed. The primary sources of noise in EV charging stations are identified, considering their design and configuration. The results of acoustic tests for specific noise sources and entire charging stations are presented, including measurements of sound pressure level (SPL), acoustic imaging, and the generated acoustic spectrum. The paper also describes noise reduction methods and proposes solutions aimed at minimizing the noise generated by charging infrastructure. Additionally, the results of tests illustrating the effectiveness of these methods are presented. Full article
(This article belongs to the Collection "Electric Vehicles" Section: Review Papers)
Show Figures

Figure 1

41 pages, 101624 KiB  
Article
Power Demand Patterns of Public Electric Vehicle Charging: A 2030 Forecast Based on Real-Life Data
by Marco Baronchelli, Davide Falabretti and Francesco Gulotta
Sustainability 2025, 17(3), 1028; https://doi.org/10.3390/su17031028 - 27 Jan 2025
Cited by 3 | Viewed by 1894
Abstract
As the adoption of electric vehicles accelerates, understanding the impact of public charging on the power grid is crucial. However, today, a notable gap exists in the literature regarding approaches capable of accurately estimating the expected influence of e-mobility power demand on electrical [...] Read more.
As the adoption of electric vehicles accelerates, understanding the impact of public charging on the power grid is crucial. However, today, a notable gap exists in the literature regarding approaches capable of accurately estimating the expected influence of e-mobility power demand on electrical grids, especially at medium and low voltage levels. To fill this gap, in this study, a procedure is proposed to estimate the power demand patterns of public car parks in a 2030 scenario. To this end, data collected from real-life car parks in Italy are used in Monte Carlo simulations, where probabilistic daily power demand curves are created with different maximum charging powers (from 7.4 kW to ultra-fast charging). The results highlight high variability in the power demand depending on the location and type of car park. City center car parks exhibit peak demand during morning hours, linked to commercial activities, while car parks near railway stations and hospitals show demand patterns aligned with transportation and healthcare needs. Business area car parks, in contrast, have a more pronounced demand during work hours on weekdays, with much lower activity during weekends. This study also demonstrates that, in some situations, ultra-fast charging can increase peak power demand from the grid by up to 210%. Given their contribution to the existing literature, the power demand patterns from this research constitute a valuable starting point for future studies aimed at quantitatively assessing the impact of e-mobility on the power system. In addition, they can effectively support decision-makers in optimally designing the e-mobility recharge infrastructure. Full article
(This article belongs to the Special Issue Modeling, Control, and Optimization of Hybrid Energy Systems)
Show Figures

Figure 1

13 pages, 3435 KiB  
Article
Factors Influencing Electric Vehicle Charging Station Locations and Policy Implications: Empirical Lessons from Seoul Metropolitan Area in Korea
by Hyunjoong Kim and Gyeong Seok Kim
Sustainability 2025, 17(2), 745; https://doi.org/10.3390/su17020745 - 18 Jan 2025
Cited by 2 | Viewed by 1980
Abstract
The growth of electric vehicle (EV) demand in Korea is closely tied to the challenge of optimal charging station placement. Despite the quantitative increase in charging stations, their uneven spatial distribution remains a significant issue, as highlighted by several related studies. This research [...] Read more.
The growth of electric vehicle (EV) demand in Korea is closely tied to the challenge of optimal charging station placement. Despite the quantitative increase in charging stations, their uneven spatial distribution remains a significant issue, as highlighted by several related studies. This research analyzes the factors influencing the location of public electric vehicle fast-charging stations (PEVFCSs) in Korea’s Seoul Metropolitan Area (SMA). Our analysis reveals that the SMA has yet to implement a systematic urban planning approach for PEVFCS placement. Interestingly, traffic volume is negatively correlated with PEVFCS location, contrary to expectations. Through a comprehensive diagnosis of the current situation, we offer valuable insights and lessons learned from the SMA experience. These findings contribute to the development of plausible policies for more effective PEVFCS distribution in urban areas. Full article
Show Figures

Figure 1

Back to TopTop