Bi-Level Optimal Dispatching Model for EV-Based Virtual Energy Storage System[J]. 中国电机工程学会电力与能源系统学报(英文), 2025,11(4):1556-1569.
Wenqian Luo, Yue Yuan, Xiaoxiao Dong, et al. Bi-Level Optimal Dispatching Model for EV-Based Virtual Energy Storage System[J]. Csee journal of power and energy systems, 2025, 11(4): 1556-1569.
Bi-Level Optimal Dispatching Model for EV-Based Virtual Energy Storage System[J]. 中国电机工程学会电力与能源系统学报(英文), 2025,11(4):1556-1569. DOI: 10.17775/CSEEJPES.2021.07520.
Wenqian Luo, Yue Yuan, Xiaoxiao Dong, et al. Bi-Level Optimal Dispatching Model for EV-Based Virtual Energy Storage System[J]. Csee journal of power and energy systems, 2025, 11(4): 1556-1569. DOI: 10.17775/CSEEJPES.2021.07520.
Bi-Level Optimal Dispatching Model for EV-Based Virtual Energy Storage System
摘要
Abstract
Owing to shifts in global energy construction
use of electric vehicles (EVs) has increased rapidly. In order to promote consumption of renewable energy and eliminate potential adverse effects of high EV penetration
this paper proposes the novel concept of an virtual energy storage system (VESS) and a corresponding bi-level optimal dispatching model. The VESS consists of all EV batteries currently connected to the grid at the same moment. Installation location of the VESS depends on distribution of available charging piles
while VESS’ capacity is variable depending on EV parking times and quantity of electric batteries. The upper level of the associated bi-level VESS dispatching model determines the VESS’ scheduling strategy
and a complex time-sequential trip chain model considering spatiotemporal EV distribution and road congestion level is proposed to obtain available VESS capacity in the distribution system. The model's lower level decides specific power allocation for each EV. Data from National Household Travel Survey 2017 (NHTS2017) and EV database are employed to mimic the VESS in the distribution network. A case study comparing EV uncontrolled charging load and optimal scheduling demonstrates that the proposed VESS dispatch strategy can consume surplus photovoltaic power and balance load fluctuation.
关键词
Keywords
references
28. U. S. Department of Transportation, Federal Highway Administration. ( 2017 ). National household travel survey. [Online]. Available: http://nhts.ornl.gov.