Open AccessCabin Temperature Regulation-based Charging Strategy for Electric Vehicles Under 5G
Author(s) -
Chen Zhao,
Chao Yang,
Cui Ziti,
Xianjun Zeng,
Fan Zifan,
Zhou You
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1754/1/012006
Subject(s) - grid , power grid , automotive engineering , peak load , power (physics) , control (management) , transmission (telecommunications) , computer science , electrical engineering , engineering , physics , geometry , mathematics , quantum mechanics , artificial intelligence
As massive EVs are introduced rapidly, large-scale disordered charging loads appear in the power grid, which may lead to "peak plus peak" and overload for local substations. With the rapid development of 5G, the data transmission of large-scale EVs is suggested to help optimizing the orderly charging strategy under cabin temperature control and load control in EVs in this paper. The charging time, charging cost and substation capacity are considered as constraints, so as to optimize the charging period of EVs. It seems that the temperature control dispatching can effectively reduce the disordered charging load of EVs, smooth the overall load curve of the power grid and result "peak shifting and valley filling" of the power grid.