OPTIMIZATION SCHEDULING OF EV CLUSTERS CONSIDERING MULTIPLE USIS AND NEW ENERGY CONSUMPTION
Cheng Jing, Luo Xu, Han Lu, Yan Jing
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Xinjiang University, Engineering Research Center of the Ministry of Education for Renewable Energy Power Generation and Grid Connection Control, Urumuqi 830017, China
In order to fully leverage the potential energy storage resource attributes of electric vehicles as flexible and schedulable power grids, an optimized scheduling strategy for electric vehicles considering multiple dimensions of user satisfaction and new energy consumption is proposed. Extract travel information from the user travel information database using Monte Carlo method and simulate its charging process, establish physical conditions and charging expectations for single user participation in scheduling, and construct satisfaction indices for electric vehicle clusters. Establish a joint scheduling model based on user satisfaction and new energy consumption, and solve it using the primal dual interior point algorithm. Based on the Swedish customer satisfaction index model, a comprehensive satisfaction model is constructed, and an evaluation mechanism for user satisfaction and new energy consumption satisfaction is established. Taking a micro-grid in Suzhou as a case study, simulation analysis and verification were conducted. The results showed that compared to only considering user satisfaction from the distribution network side, implementing a joint scheduling strategy for the micro-grid system can reduce the rate of wind and solar curtailment, significantly improve user satisfaction and new energy consumption satisfaction, and achieve friendly interaction between electric vehicles, the power grid, and new energy.
Cheng Jing, Luo Xu, Han Lu, Yan Jing.
OPTIMIZATION SCHEDULING OF EV CLUSTERS CONSIDERING MULTIPLE USIS AND NEW ENERGY CONSUMPTION[J]. Acta Energiae Solaris Sinica. 2025, 46(7): 267-278 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0459
中图分类号:
TK89
TM734
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参考文献
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