TY - JOUR
T1 - The potentials of vehicle-grid integration on peak shaving of a community considering random behavior of aggregated vehicles
AU - Li, Yalun
AU - Wang, Kun
AU - Xu, Chaojie
AU - Wu, Yu
AU - Li, Liguo
AU - Zheng, Yuejiu
AU - Yang, Shichun
AU - Wang, Hewu
AU - Ouyang, Minggao
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2025/4
Y1 - 2025/4
N2 - With large-scale electric vehicles (EVs) promoted and connected to the power grid, the uncontrolled charging of EVs enlarges the peak-valley range of load in the distribution grid. To alleviate the peak-valley range and enhance the stability of the distribution grid, vehicle-grid integration (VGI) is proposed as an economic and potential solution. However, the impact of disorderly charging and the potential of VGI considering random user behavior requires clarification. This paper established a mixed-integer linear programming model with user behavior simulated by the Monte Carlo algorithm. The travel and charging behavior of EVs are provided by Monte Carlo simulation with characteristic parameters from statistical data of urban vehicle travel data. A digital model describing the VGI charging boundary is built to restrict the transition from uncontrolled charging to VGI. Through analysis of the global optimization results, the comparison of disorderly charging with VGI under different scenarios is provided to illustrate the effectiveness of avoiding load uplift and reducing load peak-valley range. In a typical residential community with 100 EVs per 1000 people, disorderly charging increases the peak load by 17.1%, while VGI, with a participation ratio of 30%, reduces the load range by 74.8%. This study clearly demonstrates the effectiveness of VGI and guides the implementation of VGI in the rapid growth of EVs.
AB - With large-scale electric vehicles (EVs) promoted and connected to the power grid, the uncontrolled charging of EVs enlarges the peak-valley range of load in the distribution grid. To alleviate the peak-valley range and enhance the stability of the distribution grid, vehicle-grid integration (VGI) is proposed as an economic and potential solution. However, the impact of disorderly charging and the potential of VGI considering random user behavior requires clarification. This paper established a mixed-integer linear programming model with user behavior simulated by the Monte Carlo algorithm. The travel and charging behavior of EVs are provided by Monte Carlo simulation with characteristic parameters from statistical data of urban vehicle travel data. A digital model describing the VGI charging boundary is built to restrict the transition from uncontrolled charging to VGI. Through analysis of the global optimization results, the comparison of disorderly charging with VGI under different scenarios is provided to illustrate the effectiveness of avoiding load uplift and reducing load peak-valley range. In a typical residential community with 100 EVs per 1000 people, disorderly charging increases the peak load by 17.1%, while VGI, with a participation ratio of 30%, reduces the load range by 74.8%. This study clearly demonstrates the effectiveness of VGI and guides the implementation of VGI in the rapid growth of EVs.
KW - Charging boundary
KW - Mixed-integer linear programming
KW - Monte Carlo model
KW - Vehicle-grid integration (VGI)
UR - http://www.scopus.com/pages/publications/105000161381
U2 - 10.1016/j.nxener.2024.100233
DO - 10.1016/j.nxener.2024.100233
M3 - Article
AN - SCOPUS:105000161381
SN - 2949-821X
VL - 7
JO - Next Energy
JF - Next Energy
M1 - 100233
ER -