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Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids

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

Deadline for manuscript submissions: closed (29 October 2024) | Viewed by 29643

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Dr. Evangelos Karfopoulos

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Guest Editor

I-Sense Research Group, Institute of Communication and Computer Systems (ICCS), National Technical University of Athens (NTUA), Athens, Greece
Interests: EV management systems and techniques for their efficient integration in electricity grids; multi-agent energy systems; distributed optimization and control; optimal battery storage management at consumer/grid/utility scale; hybrid RES/storage planning and management
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Dr. Michele Roccotelli

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Department of Electrical and Information Engineering (DEI), Politecnico di Bari, Via Orabona, 4, 70125 Bari, Italy
Interests: smart grids; smart buildings; smart mobility; optimization and control methods
Special Issues, Collections and Topics in MDPI journals

Dr. Ioannis Karakitsios

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Guest Editor

Smart RUE Research Group, National Technical University of Athens, Athens, Greece
Interests: e-mobility (conductive and inductive charging of electric vehicles); demand-response services and issues concerning the electricity market in non-interconnected islands
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The decarbonisation of road transport and its efficient integration into the electricity grid is one of the cornerstones of energy transition. The electrification of the transport sector serves two objectives: (1) to reduce the reliance of the transport sector on fossil fuels and (2) to reduce vehicle greenhouse gas (GHG) emissions by using environmentally friendly energy sources to meet the EV charging demand.

The EV fleet becomes an increasingly important factor for power systems as new grid planning and operational challenges are raised for system operators due to their dynamic spatiotemporal charging behaviour. The challenge for system operators is not only the extra energy demand, but also the simultaneous power demand at the distribution level. Indicatively, the EV charging demand can double the yearly electricity consumption of a household, but the critical issue is that the EV (peak) power demand can be increased by five times when considering the synchronised home charging of an EV fleet at the neighbourhood level. This additional EV demand can provoke network operational issues (overloading or voltage excursions) in the existing grid infrastructure, which would require costly grid reinforcements.

The storage capacity of the battery of electric vehicles is partially exploited for daily use. The idle battery capacity can be exploited by the system/market operators or any other energy stakeholder to support the operation of the electricity grid at all voltage levels. Exploiting the full battery capacity by also considering the bidirectional power flow between the vehicle and the electricity grid will maximise the benefits for both the EV users and the electricity grid. Since the battery capacity of an individual EV is limited to offer ancillary services to the energy stakeholders, advanced (spatiotemporal) aggregation methods should be developed. The provision of ancillary services requires the development of the respective market concepts and management schemes. In addition, distributed approaches must be investigated in order to offer decentralised solutions for the charging and routing management of large EV fleets.

The scope of this Special Issue is to present advanced EV charging and management solutions, enabling the efficient integration of electric vehicles in the electricity grids at all grid levels under a mass deployment scenario.

We hope you can join us in this Special Issue by contributing original research papers and unpublished work not currently under review by any other journal/magazine/conference.

Potential topics include (but are not limited to):

Stochastic modelling of the expected grid impact of EV deployment;
Steady-state and dynamic impact analysis of the large-scale integration of EVs in electricity grids;
Enhanced network planning tools considering EV flexibility and V2G services;
Efficient charging technologies enabling the provision of ancillary services to the electricity grid or energy markets;
Advanced spatiotemporal management concepts for offering grid ancillary services;
Large-scale EV coordination schemes for offering market ancillary services;
Innovative local market models enabling vehicle-to-grid services;
Distributed or centralised EV coordination schemes;
EV/RES/storage synergy schemes;
Dynamic EV control for frequency support.

Dr. Evangelos Karfopoulos
Dr. Michele Roccotelli
Dr. Ioannis Karakitsios
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

electric vehicles
smart energy management
grid-integrated vehicles
Vehicle to grid (V2G)
Vehicle to home (V2H)
EV market participation
ancillary services
distributed coordination
EV demand forecast
large-scale coordination
frequency support
voltage support
EV/RES synergies
EV/storage synergies
microgrid
EV aggregator
EV dynamic clustering
EV charging optimisation

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Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids: 2nd Edition in Energies (1 article)

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25 pages, 3805 KiB

Open AccessArticle

Development and Implementation of a Smart Charging System for Electric Vehicles Based on the ISO 15118 Standard

by Jóni B. Santos, André M. B. Francisco, Cristiano Cabrita, Jânio Monteiro, André Pacheco and Pedro J. S. Cardoso

Energies 2024, 17(12), 3045; https://doi.org/10.3390/en17123045 - 20 Jun 2024

Cited by 6 | Viewed by 2111

Abstract

There is currently exponential growth in the electric vehicle market, which will require an increase in the electrical grid capacity to meet the associated charging demand. If, on the one hand, the introduction of energy generation from renewable energy sources can be used to meet that requirement, the intermittent nature of some of these sources will challenge the mandatory real-time equilibrium between generation and consumption. In order to use most of the energy generated via these sources, mechanisms are required to manage the charging of batteries in electric vehicles, according to the levels of generation. An effective smart charging process requires communication and/or control mechanisms between the supply equipment and the electric vehicle, enabling the adjustment of the energy transfer according to the generation levels. At this level, the ISO 15118 standard supports high-level communication mechanisms, far beyond the basic control solutions offered through the IEC 61851-1 specification. It is, thus, relevant to evaluate it in smart charging scenarios. In this context, this paper presents the development of a charge emulation system using the ISO 15118 communication protocol, and it discusses its application for demand response purposes. The system comprises several modules developed at both ends, supply equipment and electric vehicles, and allows the exchange of data during an emulated charging process. The system also includes human interfaces to facilitate interactions with users at both ends. Tests performed using the implemented system have shown that it supports a demand response when integrated with a photovoltaic renewable energy source. The dynamic adjustment to charging parameters, based on real-time energy availability, ensures efficient and sustainable charging processes, reducing the reliance on the grid and promoting the use of renewable energy. Full article

(This article belongs to the Special Issue Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids)

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15 pages, 5928 KiB

Open AccessArticle

Electrical Vehicle Smart Charging Using the Open Charge Point Interface (OCPI) Protocol

by Sylvain Guillemin, Romain Choulet, Gregory Guyot and Sothun Hing

Energies 2024, 17(12), 2873; https://doi.org/10.3390/en17122873 - 12 Jun 2024

Cited by 3 | Viewed by 1785

Abstract

This paper proposes a new approach to the design of smart charging systems. It aims to separate the role of the Smart Charging Service Provider (SCSP) from the role of the Charge Point Operator (CPO) to provide real flexibility and efficiency of mass deployment. As interoperability is required for this purpose, the challenge is to use standard equipment and protocols in the design of the smart charging Energy Management System (EMS). The use of an Open Charge Point Interface (OCPI) is crucial for an interface between the EMS and the Charge Point Operator. The smart charging EMS developed has been implemented and successfully tested with two CPOs, with different use cases: (1) EV charging infrastructure at office buildings, and (2) EV charging infrastructure installed at a public car park facility. Full article

(This article belongs to the Special Issue Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids)

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16 pages, 3038 KiB

Open AccessFeature PaperArticle

Locating and Sizing Electric Vehicle Chargers Considering Multiple Technologies

by Tommaso Schettini, Mauro dell’Amico, Francesca Fumero, Ola Jabali and Federico Malucelli

Energies 2023, 16(10), 4186; https://doi.org/10.3390/en16104186 - 18 May 2023

Cited by 8 | Viewed by 1987

Abstract

In order to foster electric vehicle (EV) adoption rates, the availability of a pervasive and efficient charging network is a crucial requirement. In this paper, we provide a decision support tool for helping policymakers to locate and size EV charging stations. We consider a multi-year planning horizon, taking into account different charging technologies and different time periods (day and night). Accounting for these features, we propose an optimization model that minimizes total investment costs while ensuring a predetermined adequate level of demand coverage. In particular, the setup of charging stations is optimized every year, allowing for an increase in the number of chargers installed at charging stations set up in previous years. We have developed a tailored heuristic algorithm for the resulting problem. We validated our algorithm using case study instances based on the village of Gardone Val Trompia (Italy), the city of Barcelona (Spain), and the country of Luxembourg. Despite the variability in the sizes of the considered instances, our algorithm consistently provided high-quality results in short computational times, when compared to a commercial MILP solver. Produced solutions achieved optimality gaps within 7.5% in less than 90 s, often achieving computational times of less than 5 s. Full article

(This article belongs to the Special Issue Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids)

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19 pages, 10330 KiB

Open AccessArticle

An Enhanced Path Planner for Electric Vehicles Considering User-Defined Time Windows and Preferences

by Maximiliano Cubillos, Mauro Dell’Amico, Ola Jabali, Federico Malucelli and Emanuele Tresoldi

Energies 2023, 16(10), 4173; https://doi.org/10.3390/en16104173 - 18 May 2023

Cited by 2 | Viewed by 1871

Abstract

A number of decision support tools facilitating the use of Electric Vehicles (EVs) have been recently developed. Due to the EVs’ limited autonomy, routing and path planning are the main challenges treated in such tools. Specifically, determining at which Charging Stations (CSs) to stop, and how much the EV should charge at them is complex. This complexity is further compounded by the fact that charging times depend on the CS technology, the EV characteristics, and follow a nonlinear function. Considering these factors, we propose a path-planning methodology for EVs with user preferences, where charging is performed at public CSs. To achieve this, we introduce the Electric Vehicle Shortest Path Problem with time windows and user preferences (EVSPPWP) and propose an efficient heuristic algorithm for it. Given an origin and a destination, the algorithm prioritizes CSs close to Points of Interest (POIs) that match user inputted preferences, and user-defined time windows are considered for activities such as lunch and spending the night at hotels. The algorithm produces flexible solutions by considering clusters of charging points (CPs) as separate CSs. Furthermore, the algorithm yields resilient paths by ensuring that recommended paths have a minimum number of CSs in their vicinity. The main contributions of our methodology are the following: modeling user-defined time windows, including user-defined weights for different POI categories, creating CSs based on clusters of CPs with sufficient proximity, using resilient paths, and proposing an efficient algorithm for solving the EVSPPWP. To facilitate the use of our methodology, the algorithm was integrated into a web interface. We demonstrate the use of the web interface, giving usage examples and comparing different settings. Full article

(This article belongs to the Special Issue Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids)

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18 pages, 3731 KiB

Open AccessArticle

Analysis of an Urban Grid with High Photovoltaic and e-Mobility Penetration

by Florian Maurer, Christian Rieke, Ralf Schemm and Dominik Stollenwerk

Energies 2023, 16(8), 3380; https://doi.org/10.3390/en16083380 - 12 Apr 2023

Cited by 4 | Viewed by 1837

Abstract

This study analyses the expected utilization of an urban distribution grid under high penetration of photovoltaic and e-mobility with charging infrastructure on a residential level. The grid utilization and the corresponding power flow are evaluated, while varying the control strategies and photovoltaic installed capacity in different scenarios. Four scenarios are used to analyze the impact of e-mobility. The individual mobility demand is modelled based on the largest German studies on mobility “Mobilität in Deutschland”, which is carried out every 5 years. To estimate the ramp-up of photovoltaic generation, a potential analysis of the roof surfaces in the supply area is carried out via an evaluation of an open solar potential study. The photovoltaic feed-in time series is derived individually for each installed system in a resolution of 15 min. The residential consumption is estimated using historical smart meter data, which are collected in London between 2012 and 2014. For a realistic charging demand, each residential household decides daily on the state of charge if their vehicle requires to be charged. The resulting charging time series depends on the underlying behavior scenario. Market prices and mobility demand are therefore used as scenario input parameters for a utility function based on the current state of charge to model individual behavior. The aggregated electricity demand is the starting point of the power flow calculation. The evaluation is carried out for an urban region with approximately 3100 residents. The analysis shows that increased penetration of photovoltaics combined with a flexible and adaptive charging strategy can maximize PV usage and reduce the need for congestion-related intervention by the grid operator by reducing the amount of kWh charged from the grid by 30% which reduces the average price of a charged kWh by 35% to 14 ct/kWh from 21.8 ct/kWh without PV optimization. The resulting grid congestions are managed by implementing an intelligent price or control signal. The analysis took place using data from a real German grid with 10 subgrids. The entire software can be adapted for the analysis of different distribution grids and is publicly available as an open-source software library on GitHub. Full article

(This article belongs to the Special Issue Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids)

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27 pages, 5724 KiB

Open AccessArticle

Optimal Placement and Sizing of Electric Vehicle Charging Infrastructure in a Grid-Tied DC Microgrid Using Modified TLBO Method

by Nandini K. Krishnamurthy, Jayalakshmi N. Sabhahit, Vinay Kumar Jadoun, Dattatraya Narayan Gaonkar, Ashish Shrivastava, Vidya S. Rao and Ganesh Kudva

Energies 2023, 16(4), 1781; https://doi.org/10.3390/en16041781 - 10 Feb 2023

Cited by 52 | Viewed by 4354

Abstract

In this work, a DC microgrid consists of a solar photovoltaic, wind power system and fuel cells as sources interlinked with the utility grid. The appropriate sizing and positioning of electric vehicle charging stations (EVCSs) and renewable energy sources (RESs) are concurrently determined to curtail the negative impact of their placement on the distribution network’s operational parameters. The charging station location problem is presented in a multi-objective context comprising voltage stability, reliability, the power loss (VRP) index and cost as objective functions. RES and EVCS location and capacity are chosen as the objective variables. The objective functions are tested on modified IEEE 33 and 123-bus radial distribution systems. The minimum value of cost obtained is USD 2.0250 × 10⁶ for the proposed case. The minimum value of the VRP index is obtained by innovative scheme 6, i.e., 9.6985 and 17.34 on 33-bus and 123-bus test systems, respectively. The EVCSs on medium- and large-scale networks are optimally placed at bus numbers 2, 19, 20; 16, 43, and 107. There is a substantial rise in the voltage profile and a decline in the VRP index with RESs’ optimal placement at bus numbers 2, 18, 30; 60, 72, and 102. The location and size of an EVCS and RESs are optimized by the modified teaching-learning-based optimization (TLBO) technique, and the results show the effectiveness of RESs in reducing the VRP index using the proposed algorithm. Full article

(This article belongs to the Special Issue Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids)

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17 pages, 5754 KiB

Open AccessArticle

How Can EVs Support High RES Penetration in Islands

by Ioannis Karakitsios, Dimitrios Lagos, Aris Dimeas and Nikos Hatziargyriou

Energies 2023, 16(1), 558; https://doi.org/10.3390/en16010558 - 3 Jan 2023

Cited by 3 | Viewed by 2224

Abstract

The electrification of the transportation sector contributes to a cleaner environment in non-interconnected island (NII) systems or standalone islands. Moreover, e-mobility can significantly contribute to achieving very high renewable energy source (RES) penetration levels in islands, allowing a reduction both in the emissions due to the conventional generation and the system’s cost. Ιncreased RES penetration, however, can pose technical challenges for an island’s system. In order to overcome these challenges, new technologies like grid-forming converters are important. Moreover, the provision of new ancillary services in relation to battery storage systems might be considered, while novel control and protection schemes are needed to ensure secure operation. E-mobility can also contribute to solving technical problems that arise from very high RES penetration by providing frequency containment reserves or reactive power compensation. Since EV charging demand introduces modifications in the system’s load curve, e-mobility may affect the power grid for long-term planning and short-term operation, i.e., line loading and voltages. The application of specifically developed smart charging methodologies can mitigate the relevant grid impact, while effective exploitation of EV–RES synergies can achieve higher RES penetration levels. This paper examines how e-mobility can contribute to increasing RES penetration in islands while considering the technical issues caused. In particular, this paper takes into account the distinct characteristics of NIIs towards the identification of solutions that will achieve very high RES penetration while also addressing the relevant technical challenges (voltage control, frequency control, short circuit protection, etc.). The effect of e-mobility in the power grid of NII systems is evaluated, while smart charging methodologies to mitigate the relevant impact and further increase RES penetration are identified. Full article

(This article belongs to the Special Issue Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids)

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18 pages, 1549 KiB

Open AccessArticle

Influence of Battery Aging on the Operation of a Charging Infrastructure

by Natascia Andrenacci, Mauro Di Monaco and Giuseppe Tomasso

Energies 2022, 15(24), 9588; https://doi.org/10.3390/en15249588 - 17 Dec 2022

Cited by 5 | Viewed by 1882

Abstract

The increasingly widespread use of electric vehicles requires proper planning of the charging infrastructure. In addition to the correct identification of the optimal positions, this concerns the accurate sizing of the charging station with respect to energy needs and the management of power flows. In particular, if we consider the presence of a renewable energy source and a storage system, we can identify strategies to maximize the use of renewable energy, minimizing the purchase costs from the grid. This study uses real charging data for some public stations, which include “normal” chargers (3 kW and 7 kW) and “quick” ones (43 kW and 55 kW), for the optimal sizing of a photovoltaic system with stationary storage. Battery degradation due to use is included in the evaluation of the overall running costs of the station. In this study, two different cost models for battery degradation and their influence on energy flow management are compared, along with their impact on battery life. Full article

(This article belongs to the Special Issue Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids)

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24 pages, 56717 KiB

Open AccessArticle

Development and Validation of V2G Technology for Electric Vehicle Chargers Using Combo CCS Type 2 Connector Standards

by Shahid Jaman, Boud Verbrugge, Oscar Hernandez Garcia, Mohamed Abdel-Monem, Blum Oliver, Thomas Geury and Omar Hegazy

Energies 2022, 15(19), 7364; https://doi.org/10.3390/en15197364 - 7 Oct 2022

Cited by 19 | Viewed by 7514

Abstract

Vehicle-to-Grid (V2G) technology is viewed as a viable solution to offer auxiliary power system services. Currently, V2G operation is only possible through DC chargers using the CHAdeMO connector with the necessary communication protocol. However, in Europe, for high-power DC charging (>50 kW), the Combined Charging Service (CCS) Type 2 is preferred over CHAdeMO. Therefore, this work presents the development of a V2G testing system with a Combo CCSType 2 charger including communication via the ISO 15118-2 protocol. The BOSCH passenger car with a 400 V battery pack is used to test and validate the technical feasibility of V2G charging via a Combo CCS Type 2 connector standard. The V2G feature is characterized in terms of efficiency, signal delay, response proportionality, magnitude accuracy and noise precision. A data driven V2G charger simulation model based on the real-time data is also developed in MATLAB/Simulink. The performance under various operating settings is presented in the outcomes, emphasizing the need for appropriate hardware calibration, and understanding while delivering standard-compliant grid control services using V2G technology. Finally, the results of the simulation model are compared with the real hardware results in terms of error, noise level and data magnitude accuracy. Full article

(This article belongs to the Special Issue Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids)

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Review

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25 pages, 5780 KiB

Open AccessReview

Autonomous and Electric Vehicles in Urban Living Labs: Smart Mobility Strategies for the Future

by Axel A. Mendoza-Armenta, Luis C. Félix-Herrán, Bartolomeo Silvestri, Andrea C. Valderrama-Solano, Juan C. Tudon-Martínez, Michele Roccotelli and Jorge de J. Lozoya-Santos

Energies 2024, 17(21), 5399; https://doi.org/10.3390/en17215399 - 30 Oct 2024

Viewed by 1728

Abstract

The deployment of electric, connected, and autonomous vehicles on public roads presents a significant challenge that can be addressed through previously established frameworks developed globally for implementing these technologies as part of an urban living lab (ULL). This systematic review, based on records from four distinct databases, focuses on projects that have conducted deployments of self-driving technologies in streets within urban environments. The review describes relevant information about various initiatives, including a classification of the stages of development reached according to the urban area covered, safety considerations, and lessons learned for optimal deployment. On-board sensing technology, digital infrastructure, and energy and communication systems emerge as the essential components of a ULL with autonomous vehicles (AVs). A crucial goal for smart cities is ensuring the scalability of large-scale deployments of such ULLs for safe, clean, and future mobility experimentation. This can only be achieved through effective coordination among academia, government, industry, and society to guarantee the successful integration of multiple projects in a unique environment. Full article

(This article belongs to the Special Issue Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids)

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