scholarly journals Efficient Online Scheduling of Electric Vehicle Charging Using a Service-Price Menu

2021 ◽  
Author(s):  
Angeliki Mathioudaki ◽  
Georgios Tsaousoglou ◽  
Emmanouel varvarigos ◽  
Dimitris Fotakis
Keyword(s):  
Quality Of Service ◽  
Electric Vehicles ◽  
Completion Time ◽  
Online Algorithm ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Guaranteed Quality ◽  
Time Minimization ◽  
Weighted Completion Time

We present an online algorithm for scheduling the charging of Electric Vehicles (EVs) in a Charging Station, aiming to optimize the overall quality of service through sum of weighted completion time minimization. Upon arrival of each EV, the algorithm generates a menu of service-price options. By letting the EV users pick their most preferable option, the algorithm offers guaranteed quality of service, achieves near optimal performance, and prevents the users from acting strategically.

scholarly journals Efficient Online Scheduling of Electric Vehicle Charging Using a Service-Price Menu

2021 ◽  
Author(s):  
Angeliki Mathioudaki ◽  
Georgios Tsaousoglou ◽  
Emmanouel varvarigos ◽  
Dimitris Fotakis
Keyword(s):  
Electric Vehicles ◽  
Completion Time ◽  
Electricity Consumption ◽  
Menu Option ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
High Penetration ◽  
Important Challenge ◽  
Charging Stations ◽  
Different Levels

Along with high penetration of Electric Vehicles (EVs), charging stations are required to service a large amount of charging requests while accounting for constraints on the station's peak electricity consumption. To this end, a charging station needs to make online charging scheduling decisions often under limited future information. An important challenge relates to the prioritization of EVs that have unknown valuations for different levels of charging services. In this paper, we take into consideration the inability of EV users to express these valuations in closed-form utility functions. We consider a paradigm where a menu of possible charging schedules and corresponding prices is generated online. By letting the EV users pick their most preferable menu option, the proposed algorithm commits on each EV's charging completion time upon its arrival, achieves a near optimal total weighted charging completion time, and prevents the users from strategically misreporting their preferences, while offering a practical and implementable solution to the problem of EVs - charging station interaction.

scholarly journals Quality of service and fairness for electric vehicle charging as a service

2021 ◽  
Vol 4 (S3) ◽  
Author(s):  
Dominik Danner ◽  
Hermann de Meer
Keyword(s):  
Quality Of Service ◽  
Electric Vehicles ◽  
Low Voltage ◽  
Energy Requirement ◽  
Capacity Allocation ◽  
Allocation Mechanism ◽  
Electric Vehicle Charging ◽  
Charging Time ◽  
Battery Capacity

AbstractDue to the increasing battery capacity of electric vehicles, European standard electricity socket-outlets at households are not enough for a full charge cycle overnight. Hence, people tend to install (semi-) fast charging wall-boxes (up to 22 kW) which can cause critical peak loads and voltage issues whenever many electric vehicles charge simultaneously in the same area.This paper proposes a centralized charging capacity allocation mechanism based on queuing systems that takes care of grid limitations and charging requirements of electric vehicles, including legacy charging control protocol restrictions. The proposed allocation mechanism dynamically updates the weights of the charging services in discrete time steps, such that electric vehicles with shorter remaining charging time and higher energy requirement are preferred against others. Furthermore, a set of metrics that determine the service quality for charging as a service is introduced. Among others, these metrics cover the ratio of charged energy to the required energy, the charging power variation during the charging process, as well as whether the upcoming trip is feasible or not. The proposed algorithm outperforms simpler scheduling policies in terms of achieved mean quality of service metric and fairness index in a co-simulation of the IEEE European low voltage grid configured with charging service requirements extracted from a mobility survey.

scholarly journals Analysis and quality of service evaluation of a fast charging station for electric vehicles

Energy ◽  
2016 ◽  
Vol 112 ◽  
pp. 669-678 ◽  
Author(s):  
Ioannis Zenginis ◽  
John S. Vardakas ◽  
Nizar Zorba ◽  
Christos V. Verikoukis
Keyword(s):  
Quality Of Service ◽  
Electric Vehicles ◽  
Service Evaluation ◽  
Charging Station ◽  
Fast Charging ◽  
Fast Charging Station

scholarly journals Efficient Online Scheduling of Electric Vehicle Charging Using a Service-Price Menu

2021 ◽  
Author(s):  
Angeliki Mathioudaki ◽  
Georgios Tsaousoglou ◽  
Emmanouel varvarigos ◽  
Dimitris Fotakis
Keyword(s):  
Electric Vehicles ◽  
Completion Time ◽  
Electricity Consumption ◽  
Menu Option ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
High Penetration ◽  
Important Challenge ◽  
Charging Stations ◽  
Different Levels

Along with high penetration of Electric Vehicles (EVs), charging stations are required to service a large amount of charging requests while accounting for constraints on the station's peak electricity consumption. To this end, a charging station needs to make online charging scheduling decisions often under limited future information. An important challenge relates to the prioritization of EVs that have unknown valuations for different levels of charging services. In this paper, we take into consideration the inability of EV users to express these valuations in closed-form utility functions. We consider a paradigm where a menu of possible charging schedules and corresponding prices is generated online. By letting the EV users pick their most preferable menu option, the proposed algorithm commits on each EV's charging completion time upon its arrival, achieves a near optimal total weighted charging completion time, and prevents the users from strategically misreporting their preferences, while offering a practical and implementable solution to the problem of EVs - charging station interaction.

scholarly journals Energy Management System Optimization of Drug Store Electric Vehicles Charging Station Operation

2021 ◽  
Vol 13 (11) ◽  
pp. 6163
Author(s):  
Yongyi Huang ◽  
Atsushi Yona ◽  
Hiroshi Takahashi ◽  
Ashraf Mohamed Hemeida ◽  
Paras Mandal ◽  
...  
Keyword(s):  
Power Generation ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
System Optimization ◽  
Mixed Integer ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Photovoltaic Power ◽  
Vehicle Charging ◽  
Charging Stations

Electric vehicle charging station have become an urgent need in many communities around the world, due to the increase of using electric vehicles over conventional vehicles. In addition, establishment of charging stations, and the grid impact of household photovoltaic power generation would reduce the feed-in tariff. These two factors are considered to propose setting up charging stations at convenience stores, which would enable the electric energy to be shared between locations. Charging stations could collect excess photovoltaic energy from homes and market it to electric vehicles. This article examines vehicle travel time, basic household energy demand, and the electricity consumption status of Okinawa city as a whole to model the operation of an electric vehicle charging station for a year. The entire program is optimized using MATLAB mixed integer linear programming (MILP) toolbox. The findings demonstrate that a profit could be achieved under the principle of ensuring the charging station’s stable service. Household photovoltaic power generation and electric vehicles are highly dependent on energy sharing between regions. The convenience store charging station service strategy suggested gives a solution to the future issues.

scholarly journals An Optimal Control Algorithm with Reduced DC-Bus Current Fluctuation for Multiple Charging Modes of Electric Vehicle Charging Station

2021 ◽  
Vol 12 (3) ◽  
pp. 107
Author(s):  
Tao Chen ◽  
Peng Fu ◽  
Xiaojiao Chen ◽  
Sheng Dou ◽  
Liansheng Huang ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Control Algorithm ◽  
Current Fluctuation ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Three Phase ◽  
Optimization Control ◽  
Dc Bus ◽  
Vehicle Charging

This paper presents a systematic structure and a control strategy for the electric vehicle charging station. The system uses a three-phase three-level neutral point clamped (NPC) rectifier to drive multiple three-phase three-level NPC converters to provide electric energy for electric vehicles. This topology can realize the single-phase AC mode, three-phase AC mode, and DC mode by adding some switches to meet different charging requirements. In the case of multiple electric vehicles charging simultaneously, a system optimization control algorithm is adopted to minimize DC-bus current fluctuation by analyzing and reconstructing the DC-bus current in various charging modes. This algorithm uses the genetic algorithm (ga) as the core of computing and reduces the number of change parameter variables within a limited range. The DC-bus current fluctuation is still minimal. The charging station system structure and the proposed system-level optimization control algorithm can improve the DC-side current stability through model calculation and simulation verification.

Scheduling Jobs with Truncated Exponential Sum-of-Logarithm-Processing-Times Based and Position-based Learning Effects

2015 ◽  
Vol 32 (04) ◽  
pp. 1550026 ◽  
Author(s):  
Yuan-Yuan Lu ◽  
Fei Teng ◽  
Zhi-Xin Feng
Keyword(s):  
Single Machine ◽  
Minimization Problem ◽  
Completion Time ◽  
Heuristic Algorithms ◽  
Exponential Sum ◽  
Total Weighted Completion Time ◽  
Learning Effects ◽  
Processing Times ◽  
Time Minimization ◽  
Weighted Completion Time

In this study, we consider a scheduling problem with truncated exponential sum-of-logarithm-processing-times based and position-based learning effects on a single machine. We prove that the shortest processing time (SPT) rule is optimal for the makespan minimization problem, the sum of the θth power of job completion times minimization problem, and the total lateness minimization problem, respectively. For the total weighted completion time minimization problem, the discounted total weighted completion time minimization problem, the maximum lateness minimization problem, we present heuristic algorithms (the worst-case bound of these heuristic algorithms are also given) according to the corresponding single machine scheduling problems without learning considerations. It also shows that the problems of minimizing the total tardiness, the total weighted completion time and the discounted total weighted completion time are polynomially solvable under some agreeable conditions on the problem parameters.

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