Modeling, Prediction and Management of Charging and Discharging Loads for Electric Vehicle–Grid Interaction under the “Double Carbon” Strategy

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Guest Editor
State Grid Jiangsu Electric Power Research Institute (EPRI), Ltd., Nanjing, China
Interests: electric vehicle integration; renewable generation

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Guest Editor
School of Electrical Engineering, Southeast University, Nanjing, China
Interests: flexible load; demand response

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Guest Editor
School of Electric Power Engineering, School of Shenguorong, Nanjing Institute of Technology, Nanjing, China
Interests: back propagation neural network; temporal convolutional network; accumulated temperature effect; information interaction; power network topology

Special Issue Information

Dear Colleagues,

The “double carbon” strategy accelerated the processes of achieving clean energy production, high energy consumption, increasingly uniform energy allocation, and gradually efficient energy use. The profound adjustment of energy pattern will definitely bring significant changes in the future development of the electric power system. In this process, electric vehicles (EVs) are vigorously promoted for their energy-saving and low-carbon advantages. However, the randomness of the load of many EVs connected to the grid will increase the peak-to-valley difference in the grid load, which will lead to serious problems such as tidal current crossing and transformer overload in the distribution network, bringing great challenges to the stable operation of the grid.

Therefore, in order to achieve the orderly charging and discharging management of EVs and to take advantage of the multiple services that they can provide to the power system, it is urgent to explore the charging and discharging load modeling, prediction, and management methods of EVs interacting with the power grid in the context of “double carbon”. How to sort out the complex influencing factors of EV load prediction, deeply explore the flexible regulation potential of EV load, study the use of virtual power plant as an important aggregation means to achieve the orderly management of EV load, and further guide the participation of EVs in energy market and auxiliary service market by means of incentive tariff are important to give a full picture of the advantages of massive EVs in the development of new power systems and energy internet constructions.

Prof. Dr. Qingshan Xu
Dr. Xiaodong Yuan
Prof. Yongbiao Yang
Prof. Dr. Haihong Bian
Guest Editors

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Keywords

  • modeling of EV energy use characteristics
  • prediction method of EV charging and discharging load considering "road–grid" integration
  • potential assessment method for EV participation in grid interaction based on new technologies such as big data and artificial intelligence
  • EV virtual power plant
  • EV with storage/DC grid/renewable energy
  • business models for EV charging and discharging management

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