Proceedings ArticleDOI
Cloud computing in electric vehicles charging control and dispatch optimization
Dan Wu,Bo Liu,Zhijian Chen,Wenyan Xie,Huang Xiang,Pei Shuwei,Bin Sheng,Donghan Feng +7 more
- pp 597-600
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TLDR
A cloud computing based schedule platform for optimal charging of electric vehicles is proposed that performs well in optimal scheduling and can also make full use of the computing resource and reduce the communication congestion.Abstract:
Charging of large-scale electric vehicles will have a significant impact on the grid so that their charging schedule needs to be optimized. The traditional centralized scheduling method requires high performance in information exchange and computing. Based on the analysis of the features of electric vehicle charging load and the research of cloud computing, we propose a cloud computing based schedule platform for optimal charging of electric vehicles. In addition, the function and implementation of the three basic modules of the platform (the data collection module, the cloud computing center and the control center) are exposed. The platform performs well in optimal scheduling for electric vehicles. In addition, the platform can also make full use of the computing resource and reduce the communication congestion.read more
Citations
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Impacts and Utilization of Electric Vehicles Integration Into Power Systems
TL;DR: In this paper, the authors carried out a literature review on plug-in electric vehicles (PEVs) integration on power system including PEVs charging load modeling,simulation and calculation, PEVs' impacts on power systems, and control and utilization of PEVs.
Journal ArticleDOI
Machine learning‐based charge scheduling of electric vehicles with minimum waiting time
TL;DR: The application of machine learning is used in selecting a charging station with available fast charging port and minimum waiting time for electric vehicles (EVs).
Journal ArticleDOI
Evaluating system architectures for driving range estimation and charge planning for electric vehicles
Adam Thor Thorgeirsson,Adam Thor Thorgeirsson,Moritz Vaillant,Stefan Scheubner,Stefan Scheubner,Frank Gauterin +5 more
TL;DR: An intelligent deployment of a range estimation software based on ML enables the application of complex, but accurate range estimation with low latencies, resulting in an improved user experience, which enhances the practicality and acceptance of BEVs.
Journal ArticleDOI
Deep learning-based power prediction aware charge scheduling approach in cloud based electric vehicular network
TL;DR: In this paper , an optimization-driven framework for EV charge scheduling in a VANET topology is presented. And the proposed fractional feedback tree algorithm (FFTA) is used to schedule charges in the EV network.
Journal ArticleDOI
Heterogeneous Aggregation and Control Modeling for Electric Vehicles With Random Charging Behaviors
TL;DR: In this article , a heterogeneous aggregation model for EVs with random charging behaviors is proposed based on the changing relation of charging power to remaining electric quantity and a variable sliding mode control model is constructed to address the randomness of the charging process and realize stable responses in a short-time scale.
References
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ReportDOI
The NIST Definition of Cloud Computing
Peter Mell,Timothy Grance +1 more
TL;DR: This cloud model promotes availability and is composed of five essential characteristics, three service models, and four deployment models.
Journal ArticleDOI
Development of an Optimal Vehicle-to-Grid Aggregator for Frequency Regulation
TL;DR: This work proposes an aggregator that makes efficient use of the distributed power of electric vehicles to produce the desired grid-scale power and applies the dynamic programming algorithm to compute the optimal charging control for each vehicle.
Journal ArticleDOI
Optimal Charging of Electric Vehicles in Low-Voltage Distribution Systems
TL;DR: In this paper, a technique based on linear programming is employed to determine the optimal charging rate for each electric vehicle in order to maximize the total power that can be delivered to the vehicles while operating within network limits.
Journal ArticleDOI
Modeling the Benefits of Vehicle-to-Grid Technology to a Power System
TL;DR: In this paper, a model of an electric vehicle storage system integrated with a standardized power system (the IEEE 30-node power system model) is described, and a decision-making strategy is established for the deployment of the battery energy stored, taking account of the state of charge, time of day, electricity prices and vehicle charging requirements.
Proceedings ArticleDOI
Optimal charging of electric vehicles in low-voltage distribution systems
TL;DR: In this paper, a technique based on linear programming is employed to determine the optimal charging rate for each electric vehicle in order to maximize the total power that can be delivered to the vehicles while operating within network limits.