期刊
IEEE ACCESS
卷 8, 期 -, 页码 5225-5235出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2019.2963692
关键词
Electric vehicles; vehicle-to-grid; battery degradation; real-time pricing; convex optimization; demand response
资金
- University of Regina
- NSERC Cohort Program
Electric vehicles (EV) are becoming increasingly popular due to their efficiency and potentials to reduce greenhouse gas emission. However, penetration of a very large number of EVs can have negative impacts on power systems. This study proposes optimal vehicle-to-grid (V2G) models to incorporate the EV penetration by minimizing multiple objectives including the peak demand, the variance of load profile, the battery degradation cost and the EV charging/discharging cost based on real-time pricing (RTP). The proposed models incorporate EV driving patterns including driving distance, driving periods, and charging/discharging levels and locations. A nonlinear battery degradation cost function is linearized and incorporated into the optimal models. In addition, a distributed control algorithm is developed to implement the optimal models. One-day simulation results show that the proposed approach can reduce the peak demand and the variance of the load profile by 7.8% and 81.9%, which can significantly improve power system stability and energy efficiency. In addition, the sum of EV charging/discharging cost and battery degradation cost is decreased from $251 to -$153. In fact, 100 EVs earn $153 in the day from the V2G program. The approaches can be used by a load aggregator or a utility to effectively incorporate EV penetration to power systems to unlock V2G opportunities and mitigate negative impacts.
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