TY - JOUR
T1 - Optimal Coordination of Electric Vehicles for Virtual Power Plants with Dynamic Communication Spectrum Allocation
AU - Zhou, Bin
AU - Zhang, Kuan
AU - Chan, Ka Wing
AU - Li, Canbing
AU - Lu, Xi
AU - Bu, Siqi
AU - Gao, Xiang
N1 - Funding Information:
Manuscript received December 21, 2019; accepted April 5, 2020. Date of publication April 13, 2020; date of current version October 23, 2020. Paper no. TII-19-5424. This work was supported in part by the National Natural Science Foundation of China under Grant 51877072 and in part by the Huxiang Young Talents Program of Hunan Province under Grant 2019RS2018. (Corresponding authors: Canbing Li; Ka Wing Chan.) Bin Zhou, Kuan Zhang, and Canbing Li are with the College of Electrical and Information Engineering and the Hunan Key Laboratory of Intelligent Information Analysis Integrated Optimization for Energy Internet, Hunan University, Changsha 410082, China (e-mail: [email protected]; [email protected]; [email protected]).
Publisher Copyright:
© 2005-2012 IEEE.
PY - 2021/1
Y1 - 2021/1
N2 - This article proposes an optimal coordinated scheduling of electric vehicles (EVs) for a virtual power plant (VPP) considering communication reliability. Recent advancements on wireless technologies offer flexible communication solutions with wide coverage and low-cost deployment for smart grid. Nevertheless, the imperfect communication may deteriorate the monitoring and controlling performance of distributed energy resources. An interactive approach is presented for combined optimization of dynamic spectrum allocation and EV scheduling in the VPP to coordinate charging/discharging strategies of massive and dispersed EVs. In the proposed approach, a dynamic partitioning model of the multi-user multi-channel cognitive radio is used to cope with the vehicle-to-grid (V2G) communication issue due to variable EV parking behaviors, and a two-stage V2G dispatch scheme is proposed for the wind-solar-EV VPP to maximize its overall daily profit. Furthermore, the effects of packet loss probability on the VPP scheduling performance and battery degradation cost are thoroughly analyzed and investigated. Comparative studies have been implemented to demonstrate the superior performance of the proposed methodology under various imperfect communication conditions.
AB - This article proposes an optimal coordinated scheduling of electric vehicles (EVs) for a virtual power plant (VPP) considering communication reliability. Recent advancements on wireless technologies offer flexible communication solutions with wide coverage and low-cost deployment for smart grid. Nevertheless, the imperfect communication may deteriorate the monitoring and controlling performance of distributed energy resources. An interactive approach is presented for combined optimization of dynamic spectrum allocation and EV scheduling in the VPP to coordinate charging/discharging strategies of massive and dispersed EVs. In the proposed approach, a dynamic partitioning model of the multi-user multi-channel cognitive radio is used to cope with the vehicle-to-grid (V2G) communication issue due to variable EV parking behaviors, and a two-stage V2G dispatch scheme is proposed for the wind-solar-EV VPP to maximize its overall daily profit. Furthermore, the effects of packet loss probability on the VPP scheduling performance and battery degradation cost are thoroughly analyzed and investigated. Comparative studies have been implemented to demonstrate the superior performance of the proposed methodology under various imperfect communication conditions.
KW - Smart grid
KW - stochastic optimization
KW - vehicle to grid
KW - virtual power plant
KW - wireless communication
UR - http://www.scopus.com/inward/record.url?scp=85096038569&partnerID=8YFLogxK
U2 - 10.1109/TII.2020.2986883
DO - 10.1109/TII.2020.2986883
M3 - Journal article
AN - SCOPUS:85096038569
SN - 1551-3203
VL - 17
SP - 450
EP - 462
JO - IEEE Transactions on Industrial Informatics
JF - IEEE Transactions on Industrial Informatics
IS - 1
M1 - 9064888
ER -
