@article{MTMT:34637645, title = {Blockchain technology in electromobility and electrification of transport}, url = {https://m2.mtmt.hu/api/publication/34637645}, author = {Zielinska, Anna}, doi = {10.15199/48.2024.01.54}, journal-iso = {PRZ ELEKTROTECHN}, journal = {PRZEGLAD ELEKTROTECHNICZNY}, volume = {100}, unique-id = {34637645}, issn = {0033-2097}, keywords = {Electric vehicle; blockchain; Electromobility; blockchain technology; development of electromobility; energy trade}, year = {2024}, eissn = {2449-9544}, pages = {259-263} } @article{MTMT:34326314, title = {Demand Response Approach for Coordinated Scheduling of EV Charging in a Micro-Grid}, url = {https://m2.mtmt.hu/api/publication/34326314}, author = {Abd El-Raouf, Ashraf and Elkholy, Mahmoud M. and Farahat, M. A. and Lotfy, Mohammed Elsayed}, doi = {10.1080/15325008.2023.2237021}, journal-iso = {ELECTR POW COMPO SYS}, journal = {ELECTRIC POWER COMPONENTS AND SYSTEMS}, unique-id = {34326314}, issn = {1532-5008}, abstract = {Compared to traditional fuel vehicles, electric vehicles (EVs) can use energy efficiently without polluting the environment, which is why environmental experts are pushing the switch to EVs. When a large number of EVs are connected to the present power grid, negative impacts to the power system dynamics may happen. Implantation of demand response (DR) programming may avoid unplanned demand peaks, and support grid voltage. The objective of this article is to minimize the cost of charging the EVs while also utilizing their battery storage capacities to support grid voltage. Price-based DR programming is used to control the EVs' charging. A study of an 8-bus distribution system with three EVs connected during charging/discharging periods, and different scenarios are simulated and compared with the grid response without any EV. New distribution tariffs have been developed to encourage small electricity users toward peak load restriction. The proposed scheduling method is valuable for the utility to estimate the capability of different control strategies for EV charging. It can also be extended to more complicated systems with large number of EVs and hence applied to a real network. MATLAB environment is used to test the suggested control scheme's robustness and efficacy.}, keywords = {Demand response; Battery capacity; Electric vehicle; power system; tariff}, year = {2023}, eissn = {1532-5016} } @article{MTMT:34326318, title = {A Review of Digital Twin Technology for Electric and Autonomous Vehicles}, url = {https://m2.mtmt.hu/api/publication/34326318}, author = {Ali, Wasim A. and Fanti, Maria Pia and Roccotelli, Michele and Ranieri, Luigi}, doi = {10.3390/app13105871}, journal-iso = {APPL SCI-BASEL}, journal = {APPLIED SCIENCES-BASEL}, volume = {13}, unique-id = {34326318}, abstract = {In the era of technological transformation, mobility and transportation systems are becoming more intelligent and greener. Thanks to powerful technologies and tools, electric and autonomous vehicles are spreading worldwide, substituting internal combustion engine vehicles and revolutionizing the way to drive. In this context, this paper is an extended version of the paper "Digital Twin in Intelligent Transportation Systems: a Review published in 2020 7th International Conference on Control, Decision and Information Technologies (CoDIT)". The aim of this paper is to provide a comprehensive review of the literature from the last five years on the use of digital twin (DT) technology for Intelligent Transportation Systems (ITSs), focusing on electric and autonomous vehicles. In particular, with respect to the previous work, the focus has been expanded to include DT integration with other cutting-edge technologies, such as the Internet of Things (IoT), Big Data, artificial intelligence (AI), machine learning (ML), and 5G for ITS. Moreover, this paper presents a broad perspective on challenges in EV applications, including tracking, monitoring, battery and charge management, connectivity, security, and privacy. In addition, this paper discusses how DT can be used to effectively address the current issues in electric vehicle services, such as tracking, monitoring, battery and charge management, connectivity, security, and privacy.}, keywords = {Electrical vehicles; Autonomous Vehicles; IoT; 5G; Big data analytics; digital twin; Intelligent Transportation System}, year = {2023}, eissn = {2076-3417}, orcid-numbers = {Roccotelli, Michele/0000-0003-3045-8920} } @article{MTMT:34326311, title = {A review of electric vehicle hosting capacity quantification and improvement techniques for distribution networks}, url = {https://m2.mtmt.hu/api/publication/34326311}, author = {Fatima, Samar and Puvi, Verner and Lehtonen, Matti and Pourakbari-Kasmaei, Mahdi}, doi = {10.1049/gtd2.13010}, journal-iso = {IET GENER TRANSM DIS}, journal = {IET GENERATION TRANSMISSION & DISTRIBUTION}, unique-id = {34326311}, issn = {1751-8687}, abstract = {The electrification of the transport sector to control the carbon footprint has been gaining momentum over the last decade with electric vehicles (EVs) seen as the replacement for conventional internal combustion engines. Economic incentives, subsidies, and tax exemptions are also paving the way for rising EV penetration in the power distribution networks. However, the exponential EV adoption requires careful technical and regulatory analysis of traditional networks to satisfy the network reliability constraints. Therefore, it would be vital to find EV hosting capacity (HC) limits of networks from a multifaceted approach involving various market players, mainly distribution system operators and EV owners. This review provides a systematic categorization of EV hosting capacity evaluation and improvement methods, thus enabling researchers and industry personnel to navigate the advancing landscape of EVs. This novel framework extends beyond the theoretical implication of diverse objective functions and HC improvement methods to the actual numerical values of EV HC across varying geographical settings. Therefore, this unique synthesis of varying aspects of EV HC facilitates the in-depth understanding of the integration of sustainable energy and transport sector.This review serves as a pioneering synthesis in the domain of EV HC estimation and future expansion possibilities by providing a unique combination of concrete data paired with the practical evaluation framework of actual distribution networks.image}, keywords = {DISTRIBUTION NETWORKS; Vehicle-to-grid; power system stability; electric vehicle charging}, year = {2023}, eissn = {1751-8695}, orcid-numbers = {Puvi, Verner/0000-0002-1342-1600} } @article{MTMT:33935272, title = {A new two-stage controller design for frequency regulation of low-inertia power system with virtual synchronous generator}, url = {https://m2.mtmt.hu/api/publication/33935272}, author = {Nour, Morsy and Magdy, Gaber and Chaves-Avila, Jose Pablo and Sanchez-Miralles, Alvaro and Jurado, Francisco}, doi = {10.1016/j.est.2023.106952}, journal-iso = {J ENERGY STORAGE}, journal = {JOURNAL OF ENERGY STORAGE}, volume = {62}, unique-id = {33935272}, issn = {2352-152X}, abstract = {This paper proposes a novel two-stage frequency-regulating control design for modern power systems consid-ering high renewable energy sources (RESs) penetration and electric vehicles (EVs). The proposed controller structure is based on a tilt fractional-order integral derivative (TFOID) in the first stage and a proportional de-rivative with filter (PDN) in the second stage, referred to as a TFOID-PDN controller. Moreover, this paper proposes a virtual synchronous generator (VSG) based on EVs' batteries that emulate the characteristics of synchronous generators and provide inertia and damping properties, thus restraining the frequency instability problem of future power systems when operating in low inertia. Furthermore, the parameters of both the pro-posed VSG and the TFOID-PDN controller are fine-tuned using a new reliable metaheuristic optimization algo-rithm called the artificial hummingbird algorithm (AHA). The efficacy of the proposed TFOID-PDN controller design is examined and investigated through a real large multi-source power system (e.g., Egyptian power system) considering the future scenario in 2035 (i.e., in the presence of high penetration levels of RESs, EVs, and different operating conditions). The superiority of the proposed AHA is validated by comparing it with other powerful optimization techniques such as the marine predators algorithm, grey wolf optimizer, and artificial bee colony optimization through designing the load frequency control based on the PID controller of a well-known two-area interconnected power system. Additionally, the proficiency of the proposed controller is verified over other controllers used in the literature, e.g., fractional-order proportional integral derivative (FOPID), tilt inte-gral derivative (TID), proportional integral derivative (PID), and proportional-integral (PI) controllers, under load/RESs fluctuations. The simulation results carried out by the MATLAB software proved the superior per-formance of the proposed TFOID-PDN controller compared to other controllers. Moreover, the proposed VSG design prevents modern power systems from reaching instability when operating with a high share of RESs and low inertia.}, keywords = {Renewable energy sources; Electric vehicles; load frequency control; power system stability; virtual synchronous generator; Two-stage controller}, year = {2023}, eissn = {2352-1538}, orcid-numbers = {Jurado, Francisco/0000-0001-8122-7415} } @article{MTMT:34326317, title = {Impacts of Community Energy Trading on Low Voltage Distribution Networks}, url = {https://m2.mtmt.hu/api/publication/34326317}, author = {Nour, Morsy and Chaves-Avila, Jose Pablo and Troncia, Matteo and Ali, Abdelfatah and Sanchez-Miralles, Alvaro}, doi = {10.1109/ACCESS.2023.3278090}, journal-iso = {IEEE ACCESS}, journal = {IEEE ACCESS}, volume = {11}, unique-id = {34326317}, issn = {2169-3536}, abstract = {The wide spread of distributed energy resources (DERs) enabled the transformation of the passive consumer to an active prosumer. One of the promising approaches for optimal management of DERs and maximizing benefits for the community and prosumers is community energy trading (CET). CET gives the prosumers the flexibility and freedom to trade electricity within the neighborhood and maximize their economic benefits besides maximizing local consumption of renewable energy sources generation. Despite the economic benefits of CET for individuals and the whole community, it could cause impacts on the low voltage distribution network (LVDN). Therefore, there is a need for a comprehensive evaluation of the potential impacts of CET on LVDN. This study compared CET with the home energy management system (HEMS) regarding community operation costs and interaction with the retailer. Furthermore, this paper focused on assessing the impacts of CET between prosumers on the phase unbalance of LVDN. Moreover, the impacts on transformer loading, lines loading, and voltage deviations are assessed. Compared to the corresponding HEMS scenarios, the results demonstrate that CET reduces the community electricity cost by up to 31%. CET resulted in better self-consumption by reducing the exports to the retailer by 93% and better self-sufficiency by covering up to 54% of energy demand by community DERs. However, CET resulted in increasing the community peak demand, accordingly, higher impacts on the LVDN. The transformer is lightly loaded in all scenarios. CET resulted in limit violations in some lines, whereas most are lightly loaded. The voltage magnitude and voltage unbalance exceeded the acceptable limits at some nodes of the LVDN.}, keywords = {Mathematical models; Energy storage; Energy storage; Costs; Energy management; Distributed energy resources; Voltage control; loading; Electric vehicles; Electric vehicle; Electricity supply industry; TRANSFORMERS; DISTRIBUTION NETWORKS; load flow; power distribution; transactive energy; transactive energy; energy community; local electricity market; energy community trading}, year = {2023}, eissn = {2169-3536}, pages = {50412-50430}, orcid-numbers = {Nour, Morsy/0000-0001-8226-5034; Chaves-Avila, Jose Pablo/0000-0002-6528-1865; Troncia, Matteo/0000-0002-9344-3593} } @article{MTMT:34326316, title = {Energy Scheduling for a DER and EV Charging Station Connected Microgrid With Energy Storage}, url = {https://m2.mtmt.hu/api/publication/34326316}, author = {Preusser, Kiraseya and Schmeink, Anke}, doi = {10.1109/ACCESS.2023.3295997}, journal-iso = {IEEE ACCESS}, journal = {IEEE ACCESS}, volume = {11}, unique-id = {34326316}, issn = {2169-3536}, abstract = {Microgrids are an effective solution to decentralize electrical grids and improve usage of distributed energy resources (DERs). Within a microgrid there are multiple active players and it can be computationally expensive to consider all their interactions. An optimal scheduler ensures that the needs within the microgrid are met without wasting electricity. With higher requirements for electric vehicle charging stations (EVCSs), schedulers are essential to ensure EV charging demands are met while being profitable and flattening peak load on the main power grid (MPG). This paper introduces two novel microgrid models, combining energy generated by a DER, the possibility of storage with an energy storage system (ESS), a load entity in the form of an EVCS and electricity trading with the MPG. The model incorporates all important environment parameters created by these players in an intelligent way that keeps the action space relatively small and thus avoiding the problems associated with a high computational complexity. These models are proven to successfully shift the load from the MPG, while still providing high customer satisfaction and throughput, in a profitable way, despite costs incurred by the DER. Instead of relying on models, real data is used, ensuring that the model is robust. Additional real world stress tests are carried out with respect to electricity costs, wind energy generation, and charging rates. Reinforcement learning is implemented to find the optimal scheduler by maximizing overall profits. In all cases considered a self-sustaining system is established, that is a more profitable and reliable EVCS.}, keywords = {Scheduling; Microgrid; reinforcement learning (RL); energy storage system (ESS); electric vehicles (EV); INDEX TERMS Distributed energy resources (DER)}, year = {2023}, eissn = {2169-3536}, pages = {73435-73447} } @article{MTMT:33935273, title = {Vector-Controlled Dual Stator Multiphase Induction Motor Drive for Energy-Efficient Operation of Electric Vehicles}, url = {https://m2.mtmt.hu/api/publication/33935273}, author = {Sowmiya, M. and Thilagar, S. Hosimin}, doi = {10.1080/03772063.2023.2175046}, journal-iso = {IETE J RES}, journal = {IETE JOURNAL OF RESEARCH}, unique-id = {33935273}, issn = {0377-2063}, abstract = {This paper proposes an Indirect Field Oriented Controlled Dual Stator Multiphase Induction Motor (IFOC-DSMIM) as a traction unit in an Electric Vehicle (EV) for the enhancement of its fuel economy and average loading capacity. The performance of the drive is studied by loading it under standard drive cycles that include free running, acceleration, and braking conditions using the MATLAB/Simulink environment. Its performance analysis is carried out to obtain efficiency curves under the three modes of excitation using a steady-state equivalent circuit approach. Studies on load sharing between the two stators, speed tracking and torque-producing capability of the drive are executed on its dynamic model and the simulation results are depicted. The average energy efficiency of the vehicle with the proposed DSMIM drive system is at least 10% higher than a Single Stator Multiphase Induction Motor (SSMIM) drive under different load percentages. Furthermore, under 75% of rated load conditions the energy efficiency is 20% higher. Thus, the proposed DSMIM configuration promises to provide a sizeable energy saving in the EV system, reducing the energy cost and increasing the driving range.}, keywords = {dynamic model; Energy efficiency; equivalent circuit; Drive cycle; efficiency curves; IFOC-DSMIM}, year = {2023}, eissn = {0974-780X} } @article{MTMT:34326313, title = {Fair and Efficient Electric Vehicle Charging Scheduling Optimization Considering the Maximum Individual Waiting Time and Operating Cost}, url = {https://m2.mtmt.hu/api/publication/34326313}, author = {Tan, Mao and Ren, Yuling and Pan, Rui and Wang, Ling and Chen, Jie}, doi = {10.1109/TVT.2023.3257547}, journal-iso = {IEEE T VEH TECHNOL}, journal = {IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY}, volume = {72}, unique-id = {34326313}, issn = {0018-9545}, abstract = {The shortage of charging piles and the soaring power demand of charging stations will lead to long waiting times for electric vehicles (EVs) that need to accomplish charging tasks. Most charging scheduling methods pay more attention to the overall waiting time, and they usually do not consider the time-aware fairness among EV users. Moreover, it has become important to schedule EVs effectively to minimize the operating cost of the station. This paper considers the trade-off between the time-aware fairness and overall waiting time of EVs to optimize the individual waiting time. A novel metric, the time-aware fairness index (TAFI), is proposed to evaluate the fairness performance for competing EVs. Therefore, a bi-objective charging and discharging scheduling problem is formulated. A novel online scheduling algorithm based on the dynamic schedulable time of EVs and the energy demand fluctuation of the station is proposed to obtain an optimal scheduling solution. Experimental results indicate that our method effectively reduces the total waiting time while minimizing the maximum individual waiting time and reducing the operating cost of the station. Moveover, the TAFI results confirm that the desired fairness behavior occurs.}, keywords = {Scheduling; Optimal scheduling; Costs; Electric vehicles; State of charge; charging stations; Vehicle-to-grid; electric vehicle charging; Charging scheduling; individual waiting time; time-aware fairness}, year = {2023}, eissn = {1939-9359}, pages = {9808-9820}, orcid-numbers = {Tan, Mao/0000-0002-2246-440X} } @article{MTMT:33415101, title = {Multiobjective Optimized Smart Charge Controller for Electric Vehicle Applications}, url = {https://m2.mtmt.hu/api/publication/33415101}, author = {Ali, Zunaib and Putrus, Ghanim and Marzband, Mousa and Gholinejad, Hamid Reza and Saleem, Komal and Subudhi, Bidyadhar}, doi = {10.1109/TIA.2022.3164999}, journal-iso = {IEEE T IND APPL}, journal = {IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS}, volume = {58}, unique-id = {33415101}, issn = {0093-9994}, abstract = {The continuous deployment of distributed energy sources and the increase in the adoption of electric vehicles (EVs) require smart charging algorithms. The existing EV chargers offer limited flexibility and controllability and do not fully consider factors (such as EV user waiting time and the length of next trip) as well as the potential opportunities and financial benefits from using EVs to support the grid, charge from renewable energy, and deal with the negative impacts of intermittent renewable generation. The lack of adequate smart EV charging may result in high battery degradation, violation of grid control statutory limits, high greenhouse emissions, and high charging cost. In this article, a neuro-fuzzy particle swarm optimization (PSO)-based novel and advanced smart charge controller is proposed, which considers user requirements, energy tariff, grid condition (e.g., voltage or frequency), renewable (photovoltaic) output, and battery state of health. A rule-based fuzzy controller becomes complex as the number of inputs to the controller increases. In addition, it becomes difficult to achieve an optimum operation due to the conflicting nature of control requirements. To optimize the controller response, the PSO technique is proposed to provide a global optimum solution based on a predefined cost function, and to address the implementation complexity, PSO is combined with a neural network. The proposed neuro-fuzzy PSO control algorithm meets EV user requirements, works within technical constraints, and is simple to implement in real time (and requires less processing time). Simulation using MATLAB and experimental results using a dSPACE digital real-time emulator are presented to demonstrate the effectiveness of the proposed controller.}, keywords = {DEGRADATION; Neural network; fuzzy logic; Costs; Renewable energy sources; Voltage control; Batteries; Real-time systems; Tariffs; Electric vehicle (EV); Battery health; smart charge controller; smart power networks}, year = {2022}, eissn = {1939-9367}, pages = {5602-5615}, orcid-numbers = {Putrus, Ghanim/0000-0002-9129-773X; Marzband, Mousa/0000-0003-3482-609X; Subudhi, Bidyadhar/0000-0003-4383-6783} } @article{MTMT:33415102, title = {Multi-unit Japanese auction for device agnostic energy management}, url = {https://m2.mtmt.hu/api/publication/33415102}, author = {Arens, Stefan and Schlueters, Sunke and Hanke, Benedikt and von Maydell, Karsten and Agert, Carsten}, doi = {10.1016/j.ijepes.2021.107350}, journal-iso = {INT J ELEC POWER}, journal = {INTERNATIONAL JOURNAL OF ELECTRICAL POWER AND ENERGY SYSTEMS}, volume = {136}, unique-id = {33415102}, issn = {0142-0615}, abstract = {The energy system is undergoing structural changes due to the integration of volatile electricity generation technology and sector coupling. This article proposes an adapted continuous Japanese auction for device agnostic energy management for a sector coupled energy system. The auction mechanism ensures that no device specific information has to be exchanged. The algorithm is implemented for a single household containing a PVsystem, a battery storage, an electric vehicle, a domestic hot water system, and a household load. For every component, a demand/supply function is proposed, which respects the respective physical characteristics. The algorithm is simulated for one year and compared to a reference, which represents an individual control of the devices without considering coordination. Further, two different auctioneers are proposed, one which focuses on energy efficient use of local resources and another one aims to reduce peak load. The results show that the proposed algorithm decreases the peak powers of the investigated system and improves local power usage, i.e. own consumption and self-sufficiency. Thus, this algorithm can reduce grid reinforcement demand due to lower peak powers by better usage of local resources, while satisfying sector coupling needs.}, keywords = {Energy storage; Energy management; Smart grid; Sector coupling}, year = {2022}, eissn = {1879-3517}, orcid-numbers = {Agert, Carsten/0000-0003-4733-5257} } @article{MTMT:33935274, title = {Smart Charging: A Comprehensive Review}, url = {https://m2.mtmt.hu/api/publication/33935274}, author = {Deb, Sanchari and Pihlatie, Mikko and Al-Saadi, Mohammed}, doi = {10.1109/ACCESS.2022.3227630}, journal-iso = {IEEE ACCESS}, journal = {IEEE ACCESS}, volume = {10}, unique-id = {33935274}, issn = {2169-3536}, abstract = {Large scale adoption and public acceptance of Electric Vehicles (EVs) require availability of charging stations. Electrification of transport has been identified as the one of the significant factors that would increase the power demand. Management of charger load has become a matter of concern for the power system engineers. Uncoordinated charging can be detrimental to the smooth operation of the power grid. On the contrary, smart charging gives certain amount of control over the charging process with respect to the power grid. Hence, adaptivity of the charging process of EVs in smart charging assists to meet the needs of power system as well as EV users. A smart charger can adjust the charging power according to the power available from the grid, EV user needs, and also support the grid during emergency. Smart charging enables EVs to act as flexible grid resources thereby providing ancillary services to the grid in case of emergency. Further, EV users can gain significant financial benefits through smart timing of their charging against spot market prices. This work presents a comprehensive overview of smart charging thereby explaining its perception, impact, user acceptance, global status and pilot projects. Also, case studies highlighting the benefits of smart charging are presented. This detailed elucidation of smart charging will assist the researchers, and experts of power industry as well as transport to find research initiatives on smart charging at one platform thereby promoting adoption of smart charging.}, keywords = {PREDICTION; review; Electric vehicle; Charging; Smart charging}, year = {2022}, eissn = {2169-3536}, pages = {134690-134703}, orcid-numbers = {Pihlatie, Mikko/0000-0001-5312-1998} } @inproceedings{MTMT:33415109, title = {Analysis of the Charging Price and Travel Time of Battery Electric Vehicles in Romania}, url = {https://m2.mtmt.hu/api/publication/33415109}, author = {Dulau, Lucian-Ioan and Bica, Dorin}, booktitle = {The 15th International Conference Interdisciplinarity in Engineering}, doi = {10.1007/978-3-030-93817-8_48}, unique-id = {33415109}, abstract = {In this paper is presented the analysis of the charging power price for battery electric vehicles in Romania. The electric vehicles can charge from regular or dedicated charging stations, so the charging duration is different. Also, the distance that has to be covered by these vehicles can be different. The charging is currently in most cases supported by economic operators like malls and hypermarkets, but in the future the users will have to pay the charging. There are considered different electric vehicles, from various manufacturers, the cost of a kWh and various distances covered in Romania. The results will be compared with the fueling cost of a petrol vehicle.}, keywords = {Power cost; Plug-in electric vehicles; Charging duration; Charging cost}, year = {2022}, pages = {522-532} } @article{MTMT:33415099, title = {Smart Charging for Electric Car-Sharing Fleets Based on Charging Duration Forecasting and Planning}, url = {https://m2.mtmt.hu/api/publication/33415099}, author = {Lo Franco, Francesco and Cirimele, Vincenzo and Ricco, Mattia and Monteiro, Vitor and Afonso, Joao L. and Grandi, Gabriele}, doi = {10.3390/su141912077}, journal-iso = {SUSTAINABILITY-BASEL}, journal = {SUSTAINABILITY}, volume = {14}, unique-id = {33415099}, abstract = {Electric car-sharing (ECS) is an increasingly popular service in many European cities. The management of an ECS fleet is more complex than its thermal engine counterpart due to the longer "refueling" time and the limited autonomy of the vehicles. To ensure adequate autonomy, the ECS provider needs high-capacity charging hubs located in urban areas where available peak power is often limited by the system power rating. Lastly, electric vehicle (EV) charging is typically entrusted to operators who retrieve discharged EVs in the city and connect them to the charging hub. The timing of the whole charging process may strongly differ among the vehicles due to their different states of charge on arrival at the hub. This makes it difficult to plan the charging events and leads to non-optimal exploitation of charging points. This paper provides a smart charging (SC) method that aims to support the ECS operators' activity by optimizing the charging points' utilization. The proposed SC promotes charging duration management by differently allocating powers among vehicles as a function of their state of charge and the desired end-of-charge time. The proposed method has been evaluated by considering a real case study. The results showed the ability to decrease charging points downtime by 71.5% on average with better exploitation of the available contracted power and an increase of 18.8% in the average number of EVs processed per day.}, keywords = {Operation modes; Electric vehicles; sustainable mobility; battery model; Smart charging; electric car-sharing; charging management system; power flows forecasting}, year = {2022}, eissn = {2071-1050}, orcid-numbers = {Ricco, Mattia/0000-0002-7482-1173; Grandi, Gabriele/0000-0002-4565-1064} } @article{MTMT:33415104, title = {Reinforcement learning-based demand-side management by smart charging of electric vehicles}, url = {https://m2.mtmt.hu/api/publication/33415104}, author = {Ozcelik, Melik Bugra and Kesici, Mert and Aksoy, Necati and Genc, Istemihan}, doi = {10.1007/s00202-022-01597-2}, journal-iso = {ELECTR ENG}, journal = {ELECTRICAL ENGINEERING}, volume = {104}, unique-id = {33415104}, issn = {0948-7921}, abstract = {In the future, the load demand due to charging of large numbers of electric vehicles (EVs) will be at such a high level that existing networks in some regions may not afford. Therefore, radical changes modernizing the grid will be required to overcome the technical and economic problems besides bureaucratic issues. Amendments to be made in the regulations on electrical energy and new tariff regulations can be considered within this scope. Smart charging of EVs is not often dealt with a solution using reinforcement learning (RL), which is one of the most effective methods for solving such decision-making problems. Most of the studies on this topic endeavor to estimate the state and action spaces and to tune the penalty coefficients within the RL models developed. In this paper, we solve the EV charging problem using expected SARSA with a novel rewarding strategy, as we propose a new approach to determine the state and action spaces. The efficacy of the proposed method is demonstrated on the problem of charging a single EV, as we compare it with a number of alternatives involving Q-Learning and constant charging approaches.}, keywords = {reinforcement learning; demand-side management; Electric vehicles; Markov decision process; Q-learning; Smart charging; Expected SARSA}, year = {2022}, eissn = {1432-0487}, pages = {3933-3942}, orcid-numbers = {Ozcelik, Melik Bugra/0000-0003-2910-3858} } @article{MTMT:33142064, title = {Comprehensive review & impact analysis of integrating projected electric vehicle charging load to the existing low voltage distribution system}, url = {https://m2.mtmt.hu/api/publication/33142064}, author = {Rahman, Syed and Khan, Irfan Ahmed and Khan, Ashraf Ali and Mallik, Ayan and Nadeem, Muhammad Faisal}, doi = {10.1016/j.rser.2021.111756}, journal-iso = {RENEW SUST ENERG REV}, journal = {RENEWABLE & SUSTAINABLE ENERGY REVIEWS}, volume = {153}, unique-id = {33142064}, issn = {1364-0321}, year = {2022}, eissn = {1879-0690}, orcid-numbers = {Rahman, Syed/0000-0002-8672-6894; Khan, Irfan Ahmed/0000-0003-2484-6169; Nadeem, Muhammad Faisal/0000-0002-1906-8924} } @article{MTMT:33134834, title = {Impact of Transportation Electrification on the Electricity Grid—A Review}, url = {https://m2.mtmt.hu/api/publication/33134834}, author = {Reza, Bayani and Arash, F. Soofi and Muhammad, Waseem and Saeed, D. Manshadi}, doi = {10.3390/vehicles4040056}, journal-iso = {VEHICLES}, journal = {VEHICLES}, volume = {4}, unique-id = {33134834}, abstract = {Transportation electrification is a pivotal factor in accelerating the transition to sustainable energy. Electric vehicles (EVs) can operate either as loads or distributed power resources in vehicleto-grid (V2G) or vehicle-to-vehicle (V2V) linkage. This paper reviews the status quo and the implications of transportation electrification in regard to environmental benefits, consumer side impacts, battery technologies, sustainability of batteries, technology trends, utility side impacts, self-driving technologies, and socio-economic benefits. These are crucial subject matters that have not received appropriate research focus in the relevant literature and this review paper aims to explore them. Our findings suggest that transitioning toward cleaner sources of electricity generation should be considered along with transportation electrification. In addition, the lower cost of EV ownership is correlated with higher EV adoption and increased social justice. It is also found that EVs suffer from a higher mile-per-hour charging rate than conventional vehicles, which is an open technological challenge. Literature indicates that electric vehicle penetration will not affect the power grid in short term but charging management is required for higher vehicle penetration in the long-term scenario. The bi-directional power flow in a V2G linkage enhances the efficiency, security, reliability, scalability, and sustainability of the electricity grid. Vehicle-to-Vehicle (V2V) charging/discharging has also been found to be effective to offload the distribution system in presence of high EV loads}, keywords = {Energy storage; Social Justice; Distribution system; Vehicle-to-Vehicle (V2V); electric vehicles (EV); Electric vehicle (EV); Vehicle-to-Grid (V2G); transportation electrification; battery technologies}, year = {2022}, eissn = {2624-8921}, pages = {1042-1079} } @article{MTMT:33415112, title = {A Study of Reduced Battery Degradation Through State-of-Charge Pre-Conditioning for Vehicle-to-Grid Operations}, url = {https://m2.mtmt.hu/api/publication/33415112}, author = {Bui, Truong M. N. and Sheikh, Muhammad and Dinh, Truong Q. and Gupta, Aniruddha and Widanalage, Dhammika W. and Marco, James}, doi = {10.1109/ACCESS.2021.3128774}, journal-iso = {IEEE ACCESS}, journal = {IEEE ACCESS}, volume = {9}, unique-id = {33415112}, issn = {2169-3536}, abstract = {Transport electrification is a key enabler to reduce fossil fuel depletion and related carbon dioxide emissions. However, critical barriers exist in terms of battery costs and their expected life. Vehicle-to-grid technology can bring benefits to both the electrical power grid and electric vehicle owners, while its practical implementation faces challenges due to the concerns over accelerated battery degradation. This paper presents a comprehensive study on reduced Lithium-ion battery degradation through state-of-charge pre-conditioning strategies that allow an electric vehicle to participate in vehicle-to-grid operations during periods in which the vehicle is parked. Energy capacity reduction of the electric vehicle battery are predicted using semi-empirical ageing models, which have been built and validated to capture the degradation behaviours of the battery with respect to both calendar and cycling ageing. Five charging strategies for battery state-of-charge pre-conditioning have been developed to evaluate the ability to mitigate battery ageing before commencing vehicle-to-grid operations. Simulation studies on battery degradation utilizing such charging mechanisms under two different operational profiles have been undertaken. The analytical results show that the proposed charging strategies do not accelerate battery degradation and are capable of mitigating the total ageing process from 7.3 - 26.7% for the first 100 days of operational life and gradually vary to 8.6 - 12.3% for one-year continual operation compared to the reference standard charging approach.}, keywords = {DEGRADATION; Aging; Costs; Electric vehicles; Batteries; Predictive models; Loss measurement; Lithium-ion battery; Vehicle-to-grid; Vehicle-to-grid; Battery degradation; semi-empirical model; SoC preconditioning; smart charge}, year = {2021}, eissn = {2169-3536}, pages = {155871-155896}, orcid-numbers = {Sheikh, Muhammad/0000-0003-4019-7031} } @article{MTMT:32405354, title = {Optimized time step for electric vehicle charging optimization considering cost and temperature}, url = {https://m2.mtmt.hu/api/publication/32405354}, author = {Dahmane, Yassir and Chenouard, Raphael and Ghanes, Malek and Alvarado-Ruiz, Mario}, doi = {10.1016/j.segan.2021.100468}, journal-iso = {SUSTAIN ENERGY GRIDS}, journal = {SUSTAINABLE ENERGY GRIDS & NETWORKS}, volume = {26}, unique-id = {32405354}, issn = {2352-4677}, abstract = {An optimal decentralized scheduling strategy for charging one Electric Vehicle (EV) is proposed to minimize the customer charging cost. Moreover, the EVs can offers more profit when considering the vehicle to grid feature, by discharging the EV in the grid at high peak demand the EV' owner can earn money and reduce his charging bill. Compared to existing methods, the main advantages of the proposed strategy is the considerations of an optimized time step. By doing so, the optimization problem uses a minimum number of decision variables and constraints. Then, the problem can be solved by all optimization method to reach the global optimum in reduced time. To formulate and solve a non-linear constrained optimization problem, the scheduling process takes into consideration: the time of arrival and time departure of the EV, the daily energy prices, the initial State of Charge (SoC) and the final SoC desired by the customer, the power limitations, and the temperature. The results obtained show a high impact of the optimal scheduling strategy and significant charging cost reduction compared to the uncontrolled charging and fixed time step algorithms. Moreover, the charging strategy only requires that each EV solves its optimization problem locally, therefore, its deployment requires a low computing capacity. (c) 2021 Elsevier Ltd. All rights reserved.}, keywords = {temperature effect; Electric vehicle; Decentralized control; LITHIUM-ION BATTERIES; Smart charging; Dynamic time step}, year = {2021}, eissn = {2352-4677} } @inproceedings{MTMT:33415100, title = {Impact of the Electrical Energy-Tariff and Vehicle-to-Grid in the Total Cost of Ownership of Electromobility Projects}, url = {https://m2.mtmt.hu/api/publication/33415100}, author = {Fernandez, Alvaro and Diaz, Matias and Rojas, Felix and Reyes-Chamorro, Lorenzo and Chavez, Hector}, booktitle = {2021 IEEE International Conference on Automation/XXIV Congress of the Chilean Association of Automatic Control (ICA-ACCA)}, doi = {10.1109/ICAACCA51523.2021.9465273}, unique-id = {33415100}, abstract = {This paper evaluates the impact of the electric power tariff on the total cost of ownership of electric vehicle purchase projects. Projects are analysed comparing electric vehicles with equivalent internal combustion engines vehicles. The annual equilibrium distance, Chilean energy tariffs, government incentives, and vehicle-to-grid utilities are considered in the analyses. Additionally, the current regulation in Chile is compared with special electrical vehicle energy tariffs applied in other countries is analysed to find possible spots to make electric vehicle projects more convenient.}, keywords = {Electric vehicles; Electromobility; total cost of ownership; energy tariffs}, year = {2021}, orcid-numbers = {Diaz, Matias/0000-0003-4489-9532; Reyes-Chamorro, Lorenzo/0000-0002-2178-0056} } @article{MTMT:32405352, title = {Review of Technical Design and Safety Requirements for Vehicle Chargers and Their Infrastructure According to National Swedish and Harmonized European Standards}, url = {https://m2.mtmt.hu/api/publication/32405352}, author = {Kersten, Anton and Rodionov, Artem and Kuder, Manuel and Hammarstrom, Thomas and Lesnicar, Anton and Thiringer, Torbjorn}, doi = {10.3390/en14113301}, journal-iso = {ENERGIES}, journal = {ENERGIES}, volume = {14}, unique-id = {32405352}, issn = {1996-1073}, abstract = {Battery electric vehicles demand a wide variety of charging networks, such as charging stations and wallboxes, to be set up in the future. The high charging power (typically in the range of a couple of kW up to a couple of hundred kW) and the possibly long duration of the charging process (up to more than 24 h) put some special requirements on the electrical infrastructure of charging stations, sockets, and plugs. This paper gives an overview of the technical design requirements and considerations for vehicle charging stations, sockets, and plugs, including their infrastructure, according to the Swedish Standard 4364000, "Low-voltage electrical installations-Rules for design and erection of electrical installations", and the corresponding harmonized European standards. In detail, the four internationally categorized charging modes are explained and the preferable charging plugs, including their two-bus communication, according to European Directives are shown. The dimensioning of the supply lines and the proper selection of the overcurrent protection device, the insulation monitor, and the residual current device are described. Furthermore, a comprehensive overview of the required safety measures, such as the application of an isolation transformer or the implementation of an overvoltage protection mechanism, and the limits for conducted electromagnetic emissions, such as low-frequency harmonics or high-frequency (150 kHz to 108 MHz) emissions, are given.}, keywords = {Electric vehicles; vehicle safety; Battery management systems; charging stations; Voltage drop; Design standards; Harmonic emissions; battery chargers; charging modes; charging plugs; charging sockets; harmonized standard; vehicle charging}, year = {2021}, eissn = {1996-1073}, orcid-numbers = {Thiringer, Torbjorn/0000-0001-5777-1242} } @article{MTMT:33415110, title = {Novel Decentralized Voltage-Centered EV Charging Control Algorithm Using DSRC System in Low Voltage Distribution Networks}, url = {https://m2.mtmt.hu/api/publication/33415110}, author = {Kriukov, Alexandru and Gavrilas, Mihai and Ivanov, Ovidiu and Grigoras, Gheorghe and Neagu, Bogdan-Constantin and Scarlatache, Florina}, doi = {10.1109/ACCESS.2021.3132419}, journal-iso = {IEEE ACCESS}, journal = {IEEE ACCESS}, volume = {9}, unique-id = {33415110}, issn = {2169-3536}, abstract = {Currently, all major vehicle manufacturers agree that the future of mobility is electric. All of them began selling electric vehicles (EVs). These types of vehicles require charging, which in turn will have an impact on power distribution systems. All the studies show that the impact on power systems will be significant and may be disastrous if there will be no investments. Unmanaged EV charging can lead to a significant increase in energy costs due to increased level of investment in energy infrastructure. This paper proposes a decentralized EV charging control (DEV-CC) system that can be executed by the existing on-board electronic control units (ECUs) and uses dedicated short-range communication (DSRC) to establish communication between EVs. The proposed DEV-CC adapts the EV charging power depending on the low-voltage distribution network (LVDN) voltage levels measured by the EVs themselves. The main purpose of the proposed DEV-CC is to charge all the EVs connected to the LVDN without allowing the voltage to drop below the imposed limit. As the results show, the proposed DEV-CC manages to charge all EVs while maintaining the voltage levels within the LVDN above the allowable limits. The proposed DEV-CC does not require any investments from the distribution system operator (DSO), can be implemented on EVs with minimal costs and is a viable solution to expensive smart grid systems.}, keywords = {INVESTMENT; Costs; Voltage control; Voltage control; Electric vehicles; State of charge; low voltage; DISTRIBUTION NETWORKS; Smart charging; low voltage distribution networks; Decentralized EV charging control system; charging power control; dedicated short-range communication}, year = {2021}, eissn = {2169-3536}, pages = {164779-164800}, orcid-numbers = {Kriukov, Alexandru/0000-0002-2490-6056; Gavrilas, Mihai/0000-0002-1075-0994; Scarlatache, Florina/0000-0003-2785-1174} } @inproceedings{MTMT:33415106, title = {Human-System Interfaces for PV-Powered Electric Vehicles Charging Station}, url = {https://m2.mtmt.hu/api/publication/33415106}, author = {Montano-Salcedo, Carlos Eduardo and Sechilariu, Manuela and Locment, Fabrice}, booktitle = {2021 IEEE 30th International Symposium on Industrial Electronics (ISIE)}, doi = {10.1109/ISIE45552.2021.9576251}, unique-id = {33415106}, abstract = {In the planning and design of a photovoltaic (PV)-Powered Electric Vehicles (EVs) Charging Station, a tool, oriented to study its technical, social, economic, and environmental aspects, has been sparsely explored or presented in the literature. Hence, the development of a graphical tool that allows to study and analyze these aspects prior to its implementation, of vital importance in the pre-development stage of this energy system and its integration with EVs. In this paper, a human-system interface (HSi) for PV-powered EVs charging stations is presented. The proposed environment is designed to analyze the energy system in three main segments: EVs' charging behavior, drive decarbonization, and grid optimization. The HSi can work in "simulation mode" and "real-time mode". In both cases, it calculates, collects, and transmits data from a MATLAB-Simulink model of a grid-connected DC microgrid. The tool displays useful information about the microgrid's status, charging behavior of EV users and the green energy adoption in each charging session.}, keywords = {Electric vehicle; Microgrid; charging station; human-system interface}, year = {2021} } @inproceedings{MTMT:33415107, title = {Framework for User-Centered Access to Electric Charging Facilities via Energy-Trading Blockchain}, url = {https://m2.mtmt.hu/api/publication/33415107}, author = {Patel, Ankit R. and Trivedi, Gargi and Vyas, Dhaval R. and Mihaita, Adriana-Simona and Padmanaban, Sanjeevikumar}, booktitle = {24th International Symposium on Wireless Personal Multimedia Communications, WPMC 2021}, doi = {10.1109/WPMC52694.2021.9700475}, unique-id = {33415107}, abstract = {In recent years, trends towards user-centered technology are increasing due to various social, economic, and environmental aspects. Concurrently, the success of electromobility is highly dependent on how we provide the charging facility and the security of energy-trading gateways. In this paper, we propose a modeling framework that would address all these challenges and would be ready for real-life implementation when data becomes available. The proposed model works on a two-charging station methodology, which allows us to examine the mutual benefits of vehicle users and electricity supply entities. In addition, the massive data revolutions and blockchain technology are providing enough impetus for the success of the given framework. Undoubtedly, this study is unique and should be considered a milestone to reveal directions for further studies.}, keywords = {TRANSPORTATION; Energy trading; infrastructure; Smart City; Electromobility; blockchain technology; Usercentered access}, year = {2021}, orcid-numbers = {Padmanaban, Sanjeevikumar/0000-0003-3212-2750} } @article{MTMT:33415111, title = {Possibilities of using blockchain technology in the area of electricity trade settlements}, url = {https://m2.mtmt.hu/api/publication/33415111}, author = {Zielinska, Anna}, doi = {10.15199/48.2021.12.32}, journal-iso = {PRZ ELEKTROTECHN}, journal = {PRZEGLAD ELEKTROTECHNICZNY}, volume = {97}, unique-id = {33415111}, issn = {0033-2097}, abstract = {The article describes the advantages and possibilities of using blockchain in various areas and sectors of the economy related to electricity trade and trading. The aim of the article is to present the components of blockchain technology that can be used in the settlement of the energy trade process, and to discuss the use of solutions based on blockchain technology that can be used in the electromobility sector and the production of energy from distributed sources. Based on literature studies, the focus was on the implementation of solutions based on blockchain technology in the process of billing electric vehicle charging and billing energy in the areas of energy clusters. The paper also specifies forecasts for the further development of the use of blockchain, electromobility and photovoltaic synergies.}, keywords = {Electric vehicle; Photovoltaic; blockchain; Electromobility; blocjchain technology; development of electromobility; energy trade}, year = {2021}, eissn = {2449-9544}, pages = {157-160} } @article{MTMT:31492258, title = {Ordered Electric Vehicles Charging Scheduling Algorithm Based on Bidding in Residential Area}, url = {https://m2.mtmt.hu/api/publication/31492258}, author = {Cheng, Xiao and Sheng, Jinma and Rong, Xiuting and Zhang, Hui and Feng, Lei and Shao, Sujie}, doi = {10.3390/info11010049}, journal-iso = {INFORMATION-BASEL}, journal = {INFORMATION (BASEL)}, volume = {11}, unique-id = {31492258}, abstract = {With the rise of electric vehicles, the key of electric vehicle charging is how to charge them in residential areas and other closed environments. Addressing this problem is extremely important for avoiding adverse effects on the load and stability of the neighboring grids where multi-user centralized charging takes place. Therefore, we propose a charging dynamic scheduling algorithm based on user bidding. First, we determine the user charging priority according to bidding. Then, we design a resource allocation policy based on game theory, which could assign charge slots for users. Due to users leaving and urgent user needs, we found an alternate principle that can improve the flexibility slot utilization of charging. Simulation results show that the algorithm could meet the priority needs of users with higher charging prices and timely responses to requests. Meanwhile, this algorithm can ensure orderly electric vehicle charging, improve power utilization efficiency, and ease pressure on grid loads.}, keywords = {Electric vehicle; bidding; charging schedule; queuing rule; alternate principle}, year = {2020}, eissn = {2078-2489}, orcid-numbers = {Shao, Sujie/0000-0003-3945-0706} } @article{MTMT:31492257, title = {The opportunity for smart charging to mitigate the impact of electric vehicles on transmission and distribution systems}, url = {https://m2.mtmt.hu/api/publication/31492257}, author = {Crozier, Constance and Morstyn, Thomas and McCulloch, Malcolm}, doi = {10.1016/j.apenergy.2020.114973}, journal-iso = {APPL ENERG}, journal = {APPLIED ENERGY}, volume = {268}, unique-id = {31492257}, issn = {0306-2619}, abstract = {A rapid increase in the number of electric vehicles is expected in coming years, driven by government incentives and falling battery prices. Charging these vehicles will add significant load to the electricity network, and it is important to understand the impact this will have on both the transmission and distribution level systems, and how smart charging can alleviate it. Here we analyse the effects that charging a large electric vehicle fleet would have on the power network, taking into account the spatial heterogeneity of vehicle use, electricity demand, and network structure. A conditional probability based method is used to model uncontrolled charging demand, and convex optimisation is used to model smart charging. Stochasticity is captured using Monte Carlo simulations. It is shown that for Great Britain's power system, smart charging can simultaneously eliminate the need for additional generation infrastructure required with 100% electric vehicle adoption, while also reducing the percentage of distribution networks which would require reinforcement from 28% to 9%. Discussion is included as to how far these results can be extended to other power systems.}, keywords = {Electric vehicles; transmission system; Distribution system; Smart charging}, year = {2020}, eissn = {1872-9118}, orcid-numbers = {Morstyn, Thomas/0000-0003-2781-9588} } @article{MTMT:31492256, title = {An Electric Vehicle Charge Scheduling Approach Suited to Local and Supplying Distribution Transformers}, url = {https://m2.mtmt.hu/api/publication/31492256}, author = {Kurniawan, Teguh and Baguley, Craig A. and Madawala, Udaya K. and Suwarno and Hariyanto, Nanang and Adianto, Yuana}, doi = {10.3390/en13133486}, journal-iso = {ENERGIES}, journal = {ENERGIES}, volume = {13}, unique-id = {31492256}, issn = {1996-1073}, abstract = {Distribution networks with high electric vehicle (EV) penetration levels can experience transformer overloading and voltage instability issues. A charge scheduling approach is proposed to mitigate against these issues that suits smart home settings in residential areas. It comprises measurement systems located at distribution transformers that communicate directly with fuzzy logic controller (FLC) systems embedded within EV supply equipment (EVSE). This realizes a reduction in data processing requirements compared to more centralized control approaches, which is advantageous for distribution networks with large numbers of transformers and EV scheduling requests. A case study employing the proposed approach is presented. Realistic driver behavior patterns, EV types, and multivariate probabilistic modeling were used to estimate EV charging demands, daily travel mileage, and plug-in times. A Monte Carlo simulation approach was developed to obtain EV charging loads. The effectiveness of mitigation in terms of reducing distribution transformer peak load levels and losses, as well as improving voltage stability is demonstrated for a distribution network in Jakarta, Indonesia.}, keywords = {fuzzy logic; Monte Carlo simulation; distribution transformer; charge scheduling}, year = {2020}, eissn = {1996-1073} } @article{MTMT:31708915, title = {Review of Positive and Negative Impacts of Electric Vehicles Charging on Electric Power Systems}, url = {https://m2.mtmt.hu/api/publication/31708915}, author = {Nour, Morsy and Chaves-Avila, Jose Pablo and Magdy, Gaber and Sanchez-Miralles, Alvaro}, doi = {10.3390/en13184675}, journal-iso = {ENERGIES}, journal = {ENERGIES}, volume = {13}, unique-id = {31708915}, issn = {1996-1073}, abstract = {There is a continuous and fast increase in electric vehicles (EVs) adoption in many countries due to the reduction of EVs prices, governments' incentives and subsidies on EVs, the need for energy independence, and environmental issues. It is expected that EVs will dominate the private cars market in the coming years. These EVs charge their batteries from the power grid and may cause severe effects if not managed properly. On the other hand, they can provide many benefits to the power grid and get revenues for EV owners if managed properly. The main contribution of the article is to provide a review of potential negative impacts of EVs charging on electric power systems mainly due to uncontrolled charging and how through controlled charging and discharging those impacts can be reduced and become even positive impacts. The impacts of uncontrolled EVs charging on the increase of peak demand, voltage deviation from the acceptable limits, phase unbalance due to the single-phase chargers, harmonics distortion, overloading of the power system equipment, and increase of power losses are presented. Furthermore, a review of the positive impacts of controlled EVs charging and discharging, and the electrical services that it can provide like frequency regulation, voltage regulation and reactive power compensation, congestion management, and improving power quality are presented. Moreover, a few promising research topics that need more investigation in future research are briefly discussed. Furthermore, the concepts and general background of EVs, EVs market, EV charging technology, the charging methods are presented.}, keywords = {Renewable energy sources; Electric vehicles; congestion management; peak shaving; V2G; uncontrolled charging; delayed charging; controlled charging; V2B; V2H; valley filling}, year = {2020}, eissn = {1996-1073}, orcid-numbers = {Nour, Morsy/0000-0001-8226-5034; Chaves-Avila, Jose Pablo/0000-0002-6528-1865; Magdy, Gaber/0000-0001-6894-695X} } @article{MTMT:31708916, title = {Different charging infrastructures along with smart charging strategies for electric vehicles}, url = {https://m2.mtmt.hu/api/publication/31708916}, author = {Sachan, Sulabh and Deb, Sanchari and Singh, Sri Niwas}, doi = {10.1016/j.scs.2020.102238}, journal-iso = {SUSTAIN CITIES SOC}, journal = {SUSTAINABLE CITIES AND SOCIETY}, volume = {60}, unique-id = {31708916}, issn = {2210-6707}, abstract = {The accelerating energy demand, growing concern regarding global warming and climate change has paved the path of electrification of the transport sector. Large scale adoption of Electric Vehicles (EVs) call for availability of sustainable and easily accessible charging infrastructure. The sporadic energy demand, different battery storage capacity and diverse penetrating patterns of electric vehicles have significantly raised the load elasticity on a power grid. Smart-grid environment promises to assist the addition of EVs into national grids by enabling both EV-charging and discharging (G2V and V2G) load. This will modify the load profile and reduce cost.This paper discusses comprehensively three basic infrastructures by which charging of EVs can be done. These infrastructures are studied and compared on the basis of some parameters. It has been found that distributed infrastructure shows best results for the charging of electric vehicles. The other two infrastructures prove costlier and increase power demand. Also, this paper examines three specific smart charging strategies and the impact of each strategy on the power system load profile and realization cost. Simulation results establish the superiority of smart charging over dumb charging.}, keywords = {Battery charging; charging infrastructure; Plug-in electric vehicles; V2G; Integration into grid}, year = {2020}, eissn = {2210-6715} } @article{MTMT:31492255, title = {Reliability Oriented Modeling and Analysis of PLC for EVs to Charging Piles Communication System Based on IPA-SAMP Impulse Noise Cancelation}, url = {https://m2.mtmt.hu/api/publication/31492255}, author = {Zhang, Liang and Chi, Shengbin and Wan, Tao and Chen, Kang and Lyu, Ling}, doi = {10.1109/ACCESS.2019.2961241}, journal-iso = {IEEE ACCESS}, journal = {IEEE ACCESS}, volume = {8}, unique-id = {31492255}, issn = {2169-3536}, abstract = {With the development of new energy technology, the number of electric vehicles (EVs) will continue to increase, which will seriously threaten the safe operation of the power grid. The V2G information interaction system can help the power grid to achieve safe and reliable operation. Therefore, under the framework of the V2G information interaction system, this paper establishes the communication system between EVs and charging piles based on power line communication (PLC), which can reduce the cost and avoid the problem that the incompatible communication interface caused by different specifications of charging piles. Due to the severe impulse noise (IN) communication environments between EVs and charging piles, the transmission performance would be seriously degraded. Hence, an improved-priori-aided sparsity adaptive matching pursuit (IPA-SAMP) is proposed to reconstruct IN. In the process of IN cancelation, the measurement vector is obtained from the null sub-carriers. In order to efficiently reconstruct IN, as the input of the IPA-SAMP algorithm, partial support are improved by the optimized threshold, which significantly improve the accuracy and robustness of the recovered IN. The proposed IPA-SAMP algorithm can effectively recover IN in the channel between EVs and charging piles, improves the reliability of the information exchange system, which is validated by computer simulations.}, keywords = {Reliability; power line communication (PLC); V2G; impulse noise (IN); improved priori-aided sparsity adaptive matching pursuit (IPA-SAMP); communication system between EVs and charging piles}, year = {2020}, eissn = {2169-3536}, pages = {4605-4614} } @inproceedings{MTMT:31578523, title = {A Smart Charging Strategy for Electric Vehicles to Increase their Hosting Capacity in Distribution Systems}, url = {https://m2.mtmt.hu/api/publication/31578523}, author = {Kamruzzaman, Md. and Benidris, M.}, booktitle = {2019 51ST NORTH AMERICAN POWER SYMPOSIUM (NAPS)}, doi = {10.1109/NAPS46351.2019.9000329}, unique-id = {31578523}, abstract = {This paper proposes a smart charging strategy for electric vehicles (ENTs) to increase their hosting capacity in distribution systems (DSs). Although EVs can be charged at both home and public charging stations, large percentages of EVs are charged at home. Therefore, coordinated charging of EVs at home has the potential to increase their hosting capacity in DSs. The proposed smart charging strategy is developed based on hourly extra available power (HEAP) of DSs and probability distribution functions of daily travel distance, charging duration, departure time, and arrival time. These distribution functions are constructed using survey data collected from several technical reports. The HEAP is calculated by taking the difference between maximum hourly loading capacities and hourly loads at each node. The proposed strategy is demonstrated on the IEEE 123 node test feeder through several case studies. The AC power flow is performed using OpenDSS to calculate the maximum hourly loading capacities and to check network constraints. Monte Carlo simulations are used to calculate the hosting capacity. The results show that the hosting capacity of EVs in the IEEE 123 node test feeder using the proposed strategy is approximately 43.2% larger than that of uncontrolled charging.}, keywords = {Electric vehicles; distribution systems; hosting capacity; Smart charging}, year = {2019}, pages = {1-6} }