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Innovations and Recent Trends in Power Systems: Smart Grids, Energy Storage Systems and Electric Vehicle Integrations

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: 25 April 2025 | Viewed by 4914

Special Issue Editors

Dr. Giuseppe Graber

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Salerno, 84084 Salerno, Italy
Interests: electronics engineering; power converters; power systems simulation; matlab simulation; energy saving; energy; smart grid; railway; batteries; energy storage; electric vehicle
Special Issues, Collections and Topics in MDPI journals
Dr. Vito Calderaro

E-Mail Website
Guest Editor
Associate Professor, Department of Industrial Engineering, University of Salerno, 84084 Salerno, Italy
Interests: power systems; distribution systems; distributed generation; protection systems and voltage regulation; storage systems for power system application
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Reducing transportation-related greenhouse gas (GHG) emissions through deep decarbonization is a foremost problem in the race against climate change. According to the International Energy Agency (IEA) data, Electric Vehicles (EV) markets are seeing exponential growth as sales exceeded 10 million in 2022. However, further developments of architectures, technologies, energy management and control strategies are required to guarantee a deep penetration of EVs in modern Power Systems. EVs and energy storage systems (ESSs), in general, need to be properly integrated in Smart Grids supporting the transition towards smart grids also considering the presence of renewable energy sources (RESs). The intent of this Special Issue is to collect innovative contributions on Power System analysis and control in presence of, ESSs, RESs and high penetration of EVs. Papers can also cover topics related to techno-economic analysis of ESSs based solutions, innovative strategies for EV smart charging and Vehicle-to-Grid (V2G), methods for integrating RESs in modern power systems considering their related uncertainty, etc. More in details, a non-exhaustive list of topics to be covered in this Special Issue are as follows: EVs grid impact analysis EV smart-charging management for peak reduction into the grid. New power and energy management strategies for V2G and ESSs in smart grids. Second life battery-based approach for ESSs integration into the grid.Integration of RESs in modern power systems.New approaches to provide ancillary services based on ESSs.Innovative control strategies for ESSs in smart grids.Techno-economic analysis of ESSs in power systems for RESs and EVs integration.Lithium-Ion batteries, fuel cells, and supercapacitors applications in modern power systems.Impact of fast and ultra-fast chargers for EVs on power systems.Optimal positioning and sizing of ESSs in smart grids.Impact on grid of wireless charging systems for EVs.Resilience assessment of smart grids in presence of ESSs, RESs and EVsLoad shedding approaches in microgrids considering RESs uncertainty. Power quality issues related to EVs charging and ESSs in smart grids.Power2gas paradigm: integration of transportation network and power system.

Dr. Giuseppe Graber
Dr. Vito Calderaro
Guest Editors

Manuscript Submission Information

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Keywords

  • energy storage systems
  • power systems
  • renewable energy sources
  • electric vehicles
  • smart grids
  • ancillary services
  • vehicle-to-grid
  • power-to-gas
  • second life batteries
  • energy management strategies

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Published Papers (4 papers)

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Research

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20 pages, 12015 KiB  
Article
Probabilistic Assessment of the Impact of Electric Vehicle Fast Charging Stations Integration into MV Distribution Networks Considering Annual and Seasonal Time-Series Data
by Oscar Mauricio Hernández-Gómez and João Paulo Abreu Vieira
Energies 2024, 17(18), 4624; https://doi.org/10.3390/en17184624 - 15 Sep 2024
Viewed by 805
Abstract
Electric vehicle (EV) fast charging stations (FCSs) are essential for achieving net-zero carbon emissions. However, their high power demands pose technical hurdles for medium-voltage (MV) distribution networks, resulting in energy losses, equipment performance issues, overheating, and unexpected tripping. Integrating FCSs into the grid [...] Read more.
Electric vehicle (EV) fast charging stations (FCSs) are essential for achieving net-zero carbon emissions. However, their high power demands pose technical hurdles for medium-voltage (MV) distribution networks, resulting in energy losses, equipment performance issues, overheating, and unexpected tripping. Integrating FCSs into the grid requires considering annual and seasonal variations in EV fast-charging energy consumption. Neglecting these variations can lead to either underestimating or overestimating the impacts of FCSs on the networks. This paper introduces a probabilistic method to assess voltage profile violations, overload capacity, and increased power losses due to FCSs. By incorporating annual and seasonal time-series data, the method accounts for uncertainties related to EV fast charging. Applied to an MV feeder in Brazil, our evaluations highlight the impact of annual power consumption seasonality on EV-grid integration studies. Considering seasonal dependency is crucial for precise impact assessments of MV distribution networks. The proposed method aids utility engineers and planners in quantifying and mitigating the effects of EV fast charging, contributing to more reliable MV grid integration strategies. Full article
(This article belongs to the Special Issue Innovations and Recent Trends in Power Systems: Smart Grids, Energy Storage Systems and Electric Vehicle Integrations)
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20 pages, 6988 KiB  
Article
Mitigating Voltage Drop and Excessive Step-Voltage Regulator Tap Operation in Distribution Networks Due to Electric Vehicle Fast Charging
by Oscar Mauricio Hernández-Gómez, João Paulo Abreu Vieira, Jonathan Muñoz Tabora and Luiz Eduardo Sales e Silva
Energies 2024, 17(17), 4378; https://doi.org/10.3390/en17174378 - 1 Sep 2024
Viewed by 905
Abstract
Electric vehicles (EVs) are transforming the transportation sector, driven by the rapid expansion of charging infrastructure, including fast-charging stations (FCSs), significantly reducing charging time compared to standard charging stations. Despite the advantages of faster charging, the substantial power demand of EVs poses significant [...] Read more.
Electric vehicles (EVs) are transforming the transportation sector, driven by the rapid expansion of charging infrastructure, including fast-charging stations (FCSs), significantly reducing charging time compared to standard charging stations. Despite the advantages of faster charging, the substantial power demand of EVs poses significant technical challenges for distribution networks. In particular, the existing literature has a research gap regarding how FCSs may impact or interact with step-voltage regulators’ (SVRs) tap operations. In this study, we characterize and evaluate the effects of fast recharging at varying penetration levels (PLs) on SVRs’ tap operations using probabilistic simulations and sensitivity analysis. To address these challenges, we propose a local and innovative application of the Volt/Var control on EV fast charging. The proposed application aims to inject reactive power into the network, depending on the FCS’s nominal active power, when the bus voltage connected to the FCS exceeds a minimum value. Our research on an actual feeder in northern Brazil reveals that reducing the active power supplied to the vehicle or oversizing the charging station power converters is unnecessary. Furthermore, our strategy reduces the probability of undervoltage violations and minimizes SVR tap changes, mitigating EVs’ impact on voltage quality. Full article
(This article belongs to the Special Issue Innovations and Recent Trends in Power Systems: Smart Grids, Energy Storage Systems and Electric Vehicle Integrations)
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15 pages, 1889 KiB  
Article
Investment Decision for Long-Term Battery Energy Storage System Using Least Squares Monte Carlo
by Kyungcheol Shin and Jinyeong Lee
Energies 2024, 17(9), 2019; https://doi.org/10.3390/en17092019 - 25 Apr 2024
Cited by 1 | Viewed by 959
Abstract
The use of renewable energy sources to achieve carbon neutrality is increasing. However, the uncertainty and volatility of renewable resources are causing problems in power systems. Flexible and low-carbon resources such as Energy Storage Systems (ESSs) are essential for solving the problems of [...] Read more.
The use of renewable energy sources to achieve carbon neutrality is increasing. However, the uncertainty and volatility of renewable resources are causing problems in power systems. Flexible and low-carbon resources such as Energy Storage Systems (ESSs) are essential for solving the problems of power systems and achieving greenhouse gas reduction goals. However, ESSs are not being installed because of Korea’s fuel-based electricity market. To address this issue, this paper presents a method for determining the optimal investment timing of Battery Energy Storage Systems (BESSs) using the Least Squares Monte Carlo (LSMC) method. A case study is conducted considering the System Marginal Price (SMP) and Capacity Payment (CP), which are electricity rates in Korea. Revenue is calculated through the arbitrage of a 10 MW/40 MWh lithium-ion BESS, and linear programming optimization is performed for ESS scheduling to maximize revenue. The ESS revenue with uncertainty is modeled as a stochastic process using Geometric Brownian Motion (GBM), and the optimal time to invest in an ESS is determined using an LSMC simulation considering investment costs. The proposed method can be used as a decision-making tool for ESS investors to provide information on facility investments in arbitrage situations. Full article
(This article belongs to the Special Issue Innovations and Recent Trends in Power Systems: Smart Grids, Energy Storage Systems and Electric Vehicle Integrations)
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Review

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33 pages, 9432 KiB  
Review
Modeling of Lithium-Ion Batteries for Electric Transportation: A Comprehensive Review of Electrical Models and Parameter Dependencies
by Giuseppe Graber, Simona Sabatino, Vito Calderaro and Vincenzo Galdi
Energies 2024, 17(22), 5629; https://doi.org/10.3390/en17225629 - 11 Nov 2024
Viewed by 444
Abstract
The power and transportation sectors contribute to more than 66% of global carbon emissions. Decarbonizing these sectors is critical for achieving a zero-carbon economy by mid-century and mitigating the most severe impacts of climate change. Battery packs, which enable energy storage in electric [...] Read more.
The power and transportation sectors contribute to more than 66% of global carbon emissions. Decarbonizing these sectors is critical for achieving a zero-carbon economy by mid-century and mitigating the most severe impacts of climate change. Battery packs, which enable energy storage in electric vehicles, are a key component of electrified transport systems. The production of these batteries has significantly increased in recent years to meet rising demand, and this trend is expected to continue. However, current traction batteries exhibit lower energy density compared to fossil fuels. As a result, accurate battery models that balance computational complexity and precision are essential for designing high-performance energy storage systems. This paper provides a comprehensive review of the most used electrical models for lithium-ion batteries in traction applications, as reported in the technical literature. By exploring the strengths and limitations of different modeling approaches, this paper aims to offer valuable insights into their practical applicability for the electrification of transportation systems. Additionally, this paper discusses the primary methods employed to derive the values of the electrical components within these models. Finally, it examines the key parameters—such as temperature, state of charge, and aging—that significantly influence the component values. Ultimately, it guides researchers and practitioners in selecting the most suitable modeling approach for their specific needs. Full article
(This article belongs to the Special Issue Innovations and Recent Trends in Power Systems: Smart Grids, Energy Storage Systems and Electric Vehicle Integrations)
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