Study on energy management model of integrated New Energy-Storage-Charging system considering the influence of uncertainties

被引:4
|
作者
Liu, Huanan [1 ]
Jiang, Jing [1 ]
Zhan, Shuo [1 ]
Yang, Xiuyu [1 ]
Yu, Dongmin [2 ]
Yan, Gangui [1 ]
机构
[1] Northeast Elect Power Univ, Key Lab Modern Power Syst Simulat & Control & Rene, Minist Educ, Jilin 132012, Jilin, Peoples R China
[2] Nanchang Univ, Nanchang 330031, Jiangxi, Peoples R China
关键词
New energy; Electric vehicle charging station; Downside risk; Demand response; System uncertainty; ELECTRIC VEHICLES; DISTRIBUTION NETWORKS; TO-VEHICLE; OPERATION; AGGREGATION; STRATEGY;
D O I
10.1016/j.fuel.2022.125784
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The energy management of the integrated New energy-Storage-Charging system is affected by many source-side and load-side uncertainties, making it difficult for the system operator to choose an appropriate operation scheme. To deal with the influence of various uncertainties on the operation optimization effect of the integrated New energy-Storage-Charging system and provide an effective theoretical basis for the system operator to formulate the operation scheme, this paper studies the energy management of the integrated New energyStorage-Charging system considering various uncertain factors. First, it constructs an equipment operation model of the integrated New energy-Storage-Charging system and charging load regulation model of the electric vehicle and analyzes the influence of five uncertainties such as temperature, light intensity, wind speed, load, and electricity price on the system operation. Then, considering the load transfer cost, it establishes the energy management model of the integrated New energy-Storage-Charging system to minimize the system operation cost. Finally, based on the downside risk theory, it constructs a risk management model of the system operation considering multi-dimensional uncertainty. By imposing constraints for uncertainty management, we have the system operation optimization schemes under different risk levels. The case analysis shows that the optimization proposed in this paper can accurately adjust a load of electric vehicles to a single vehicle and reduce the operation cost of the system by participating in the demand response by load regulation. In addition, this paper proposes an effective quantitative description method and risk dealing scheme for the influence of various uncertainties.
引用
收藏
页数:15
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