Open AccessAggregation Optimization Method of Virtual Energy Storage for Electric Vehicles Considering User Elasticity
Author(s) -
Lu Liu,
Meng Niu,
Bei Li,
Yue Zhang,
Mengjiao Zou,
Dunnan Liu,
Tingting Zhang,
Lingxiang Wang,
Shanshan Shang,
Mingguang Liu
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/647/1/012130
Subject(s) - demand response , smart grid , electric vehicle , incentive , electricity , price elasticity of demand , grid , automotive engineering , computer science , vehicle to grid , engineering , electrical engineering , power (physics) , economics , microeconomics , physics , geometry , mathematics , quantum mechanics
With the continuous development of electric vehicle charging facilities, the impact of electric vehicles on the power grid is growing. Considering the automatic demand response technology of smart grid, charging pile operators participate in the demand response plan and guide users to charge according to the price signal or incentive mechanism, which can ensure the safety of the power grid and reduce the negative effects of electric vehicles on the grid influence. Based on the theory of demand side response elasticity, this paper analyzes the whole process of electric vehicle users' participation in demand response and its influencing factors, classifies electric vehicle users based on demand response, and then quantitatively analyzes users' demand response from the perspective of electricity price elasticity and consumption psychology. Finally, the demand side response model with user participation is established. The application of the model can effectively improve the enthusiasm of electric vehicle users to participate in demand side response, and reduce the negative impact of electric vehicles on the power grid.