Distributed Source-Load-Storage Cooperative Low-Carbon Scheduling Strategy Considering Vehicle-to-Grid Aggregators  

作　　者：Xiao Xu Ziwen Qiu Teng Zhang Hui Gao 

机构地区：[1]School of Automation,Nanjing University of Posts and Telecommunications,Nanjing,210023,China

出　　处：《Journal of Modern Power Systems and Clean Energy》2024年第2期440-453,共14页现代电力系统与清洁能源学报（英文）

基　　金：partially supported by the National Natural Science Foundation of China(General Program)(No.52077107);Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(No.NY220082).

摘　　要：The vehicle-to-grid(V2G)technology enables the bidirectional power flow between electric vehicle(EV)batteries and the power grid,making EV-based mobile energy storage an appealing supplement to stationary energy storage systems.However,the stochastic and volatile charging behaviors pose a challenge for EV fleets to engage directly in multi-agent cooperation.To unlock the scheduling potential of EVs,this paper proposes a source-load-storage cooperative low-carbon scheduling strategy considering V2G aggregators.The uncertainty of EV charging patterns is managed through a rolling-horizon control framework,where the scheduling and control horizons are adaptively adjusted according to the availability periods of EVs.Moreover,a Minkowski-sum based aggregation method is employed to evaluate the scheduling potential of aggregated EV fleets within a given scheduling horizon.This method effectively reduces the variable dimension while preserving the charging and discharging constraints of individual EVs.Subsequently,a Nash bargaining based cooperative scheduling model involving a distribution system operator(DSO),an EV aggregator(EVA),and a load aggregator(LA)is established to maximize the social welfare and improve the low-carbon performance of the system.This model is solved by the alternating direction method of multipliers(ADMM)algorithm in a distributed manner,with privacy of participants fully preserved.The proposed strategy is proven to achieve the objective of low-carbon economic operation.

关 键 词：Electric vehicle(EV) low-carbon scheduling mobile storage system Nash bargaining power flexibility alternating direction method of multipliers(ADMM). 

分 类 号：U491.8[交通运输工程—交通运输规划与管理] TM73[交通运输工程—道路与铁道工程]