scholarly journals EV Smart Charging with Advance Reservation Extension to the OCPP Standard

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3263
Author(s):  
Simone Orcioni ◽  
Massimo Conti
Keyword(s):  
Electric Vehicle ◽  
Power Grid ◽  
Smartphone App ◽  
Advance Reservation ◽  
End User ◽  
Charging Station ◽  
Smart Charging ◽  
Central Station ◽  
Grid Management ◽  
Charge Point

An accurate management of the interactions among end user, electric vehicle, and charging station during recharge is fundamental for the diffusion of electric mobility. The paper proposes an extension of the Open Charge Point Protocol standard with the aim of including the user in the charging optimization process. The user negotiates with the central station a recharge reservation giving his/her preference and flexibility. The charging station management system provides different solutions based on user’s flexibility. This negotiation allows the optimization of the power grid management considering the user requests and constraints. The complete architecture has been designed, implemented on a web server and on a smartphone app, and tested. Results are reported in this work.

scholarly journals Electric vehicle dispatching in smart charging station: a pricing strategy

2021 ◽  
Vol 675 (1) ◽  
pp. 012163
Author(s):  
Xuliang Zhao ◽  
Jiguang Xue ◽  
Tong Wu ◽  
Hong Xue ◽  
Sitong Dong ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Pricing Strategy ◽  
Vehicle Dispatching ◽  
Charging Station ◽  
Smart Charging

scholarly journals Flexibility of Electric Vehicle Demand: Analysis of Measured Charging Data and Simulation for the Future

2019 ◽  
Vol 10 (1) ◽  
pp. 14 ◽  
Author(s):  
Marte K. Gerritsma ◽  
Tarek A. AlSkaif ◽  
Henk A. Fidder ◽  
Wilfried G.J.H.M. van Sark
Keyword(s):  
Electric Vehicle ◽  
Congestion Management ◽  
Charging Station ◽  
Smart Charging ◽  
Vehicle Demand ◽  
High Flexibility ◽  
Charging Stations ◽  
High Scenario ◽  
Evening Peak

This paper proposes a method for analyzing and simulating the time-dependent flexibility of electric vehicle (EV) demand. This flexibility is influenced by charging power, which depends on the charging stations, the EV characteristics, and several environmental factors. Detailed charging station data from a Dutch case study have been analysed and used as input for a simulation. In the simulation, the interdependencies between plug-in time, connection duration, and required energy are respected. The data analysis of measured data reveals that 59% of the aggregated EV demand can be delayed for more than 8 h, and 16% for even more than 24 h. The evening peak shows high flexibility, confirming the feasibility of congestion management using smart charging within flexibility constraints. The results from the simulation show that the average daily EV demand increases by a factor 21 between the ‘Present-day’ and the ‘High’ scenario, while the maximum EV demand peak increases only by a factor 6, as a result of the limited simultaneity of the transactions. Further, simulations using the average charging power of individual measured transactions yield more accurate results than simulations using a fixed value for charging power. The proposed method for simulating future EV flexibility provides a basis for testing different smart charging algorithms.

scholarly journals Multiport Converter based EV Charging Station with PV and Battery

2021 ◽  
Vol 9 (VI) ◽  
pp. 2518-2521
Author(s):  
Priya A. Khobragade
Keyword(s):  
Large Scale ◽  
Power Grid ◽  
Storage System ◽  
Charging Station ◽  
Multiport Converter ◽  
Smart Charging ◽  
Fast Charging ◽  
Electrical Vehicle ◽  
Ev Charging ◽  
Fast Charging Station

: As a ecofriendly electrical vehicle, is vehicles that are used electric motor or traction motor. Are receiving widespread attention around the world due to their improved performance and zero carbon emission . The electric vehicle depend on photovoltaic and battery energy storage system . Electric vehicles include not limited road and railways. It consist of many electric appliances for use in domestic and industrial purposes that is electric car ,electric bike ,electric truck ,electric trolley bus , electric air craft ,electric space craft.The main Moto of this paper is a modelling of proposed system smart charging for electrical vehicle insuring minimum stress on power grid . The large scale development of electrical vehicle we need electric charging station for example fast charging station and super-fast charging station . During a peak demand load , large load on charging station due to the voltage sag , line fault and stress on power grid . At this all problem avoid by multiport converter based EV charging station with PV and BES by using analysis of MATLAB simulation. Result and conclusion of this paper to reduce losses improving efficiency of solar energy , no pollution (reduce) fast charging as possible as without any disturbance.

scholarly journals Optimal Planning of Electric Vehicle Charging Station Considering Mutual Benefit of Users and Power Grid

2021 ◽  
Vol 12 (4) ◽  
pp. 244
Author(s):  
Hui Hou ◽  
Junyi Tang ◽  
Bo Zhao ◽  
Leiqi Zhang ◽  
Yifan Wang ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Electric Vehicle ◽  
Power Grid ◽  
Particle Swarm ◽  
Optimal Planning ◽  
Mutual Benefit ◽  
Swarm Optimization ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Charging Stations

A reasonable plan for charging stations is critical to the widespread use of electric vehicles. In this paper, we propose an optimal planning method for electric vehicle charging stations. First of all, we put forward a forecasting method for the distribution of electric vehicle fast charging demand in urban areas. Next, a new mathematical model that considers the mutual benefit of electric vehicle users and the power grid is set up, aiming to minimize the social cost of charging stations. Then, the model is solved by the Voronoi diagram combined with improved particle swarm optimization. In the end, the proposed method is applied to an urban area, simulation results demonstrate that the proposed method can yield optimal location and capacity of each charging station. A contrasting case is carried out to verify that improved particle swarm optimization is more effective in finding the global optimal solution than particle swarm optimization.

scholarly journals DC-Microgrid Operation Planning for an Electric Vehicle Supply Infrastructure

2019 ◽  
Vol 9 (13) ◽  
pp. 2687 ◽  
Author(s):  
Benedetto Aluisio ◽  
Sergio Bruno ◽  
Luca De Bellis ◽  
Maria Dicorato ◽  
Giuseppe Forte ◽  
...  
Keyword(s):  
Power Systems ◽  
Electric Vehicle ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Operation Planning ◽  
Energy Storage Devices ◽  
Dc Microgrid ◽  
Charging Station ◽  
Smart Charging ◽  
Non Linear

The integration of electric vehicles (EVs) in power systems can be encouraged by charging station diffusion. These stations can perform smart charging processes, and can take advantage of the involvement of distributed generation sources in a microgrid framework. Furthermore, since photovoltaic batteries and EVs are sources based on direct current (DC), the realization of a DC microgrid structure is promising, though challenging. In this paper, a mixed-integer linear procedure for determining optimal operation planning of a DC-based electric vehicle supply infrastructure is proposed. The procedure aims at optimizing daily operational costs, based on forecast of photovoltaic production and EV exploitation. Peculiar aspects of energy storage devices and of the DC microgrid framework are accounted for through a non-linear iterative procedure. The proposed approach is applied to a test DC microgrid on different operation days and its effectiveness is compared to non-linear formulation solved by means of a genetic algorithm.

scholarly journals An Off-Board Multi-Functional Electric Vehicle Charging Station for Smart Homes: Analysis and Experimental Validation

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 1864
Author(s):  
Vitor Monteiro ◽  
Pedro Lima ◽  
Tiago J. C. Sousa ◽  
Julio S. Martins ◽  
Joao L. Afonso
Keyword(s):  
Electric Vehicle ◽  
Experimental Validation ◽  
Reactive Power ◽  
Control Strategies ◽  
Power Grid ◽  
Smart Homes ◽  
Current Control ◽  
Current Harmonics ◽  
Charging Station ◽  
Electric Vehicle Charging

This paper presents the analysis and experimental validation of a single-phase off-board multi-functional electric vehicle (EV) charging station (MF-EVCS), which has a single ac interface and two dc interfaces. As innovative aspects, the proposed MF-EVCS handles the interface of the ac power grid, the dc interface of a renewable energy source (RES), as well as the dc interface of an EV to perform dc charging or discharging of the batteries (in off-board grid-to-vehicle (G2V) or vehicle-to-grid (V2G) modes). Considering the power grid, the individual operation modes of the RES and the EV interfaces can be considered. Moreover, a combination of these modes is also possible. Besides, the MF-EVCS has as key innovative aspect the possibility of operating as an active power filter (APF), supporting the operation with reactive power and/or selected current harmonics. This possibility can be associated with any of the previous mentioned modes. These new features are framed in two distinct scenarios: in a smart home, where the ac-side current can be determined as a function of the other electrical appliances; in a smart grid, where the ac-side current can be determined as a requisite of the power grid. The proposed power theory, as well as the current control strategies for both ac-side and dc-side of the MF-EVCS, are presented in the paper for all the possible operation scenarios. A laboratory prototype was developed to validate the proposed MF-EVCS and the experimental results confirm its suitability for smart homes.

scholarly journals Implementation of OCPP Protocol for Electric Vehicle Applications

2019 ◽  
Vol 87 ◽  
pp. 01008
Author(s):  
Thota Venkata Pruthvi ◽  
Niladri Dutta ◽  
Phaneendra Babu Bobba ◽  
B Sai Vasudeva
Keyword(s):  
Electric Vehicle ◽  
Charging Infrastructure ◽  
Base Level ◽  
Industry Standards ◽  
Smart Charging ◽  
Electrical Vehicle ◽  
Key Factor ◽  
Software And Hardware ◽  
Charging Stations ◽  
Charge Point

The ability of the software and hardware systems to interchange information is a key factor for the success of the electric vehicle industry. Standards have been developed and are in use to ensure base level interoperability of the front-end communication and signaling processes for smart charging between electric vehicles and charge stations. The Open Charge Alliance (OCA), a group of European industries, have developed an open source common back-end protocol, called Open Charge Point Protocol (OCPP), for charging stations to reduce and secure overall investment costs. OCPP intends to enable grid services based on smart charging. In this paper the authors provide a review of the functionalities OCPP offers and how it can be used in the electrical vehicle-charging infrastructure.

scholarly journals System architecture to select the charging station by optimizing the travel time considering the destination of electric vehicle drivers in smart cities

2020 ◽  
Vol 9 (1) ◽  
pp. 273-283
Author(s):  
Ibrahim El-fedany ◽  
Driss Kiouach ◽  
Rachid Alaoui
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Smart Cities ◽  
Time Of Arrival ◽  
Advance Reservation ◽  
The Road ◽  
Charging Station ◽  
Charging Time ◽  
On The Road ◽  
Charging Stations

The main limitations of electric vehicles are the limited scope of the battery and their relatively long charging times. This may cause discomfort to drivers of electric vehicles due to a long waiting period at the service of the charging station, during their trips. In this paper, we suggest a model system based on argorithms, allowing the management of charging plans of electric vehicles to travel on the road to their destination in order to minimize the duration of the drivers' journey. The proposed system decision to select the charging station, during advance reservation of electric vehicles, take into account the time of arrival of electric vehicles at charging stations, the expected charging time at charging stations, the local status of the charging stations in real time, and the amount of energy sufficient for the electric vehicle to arrive at the selected charging station. Furthermore, the system periodically updates the electric vehicule reservations to adjust their recharge plans, when they reach their selected earlier station compared to other vehicules requesting new reservations, or they may not arrive as they were forecast, due to traffic jams on the road or certain reluctance on the part of the driver.

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