Time-of-use Pricing Model Considering Wind Power Uncertainty  

作　　者：Gang Zhang Ye Yan Kaoshe Zhang Pingli Li Meng Li Qiang He Hailiang Chao 

机构地区：[1]State Key Laboratory of Eco-Hydraulics in Northwest Arid Region,Xi'an University of Technology,Xi'an 710048,China [2]Institute of Electrical Engineering,Xi'an University of Technology,Xi'an 710048,China [3]Shaanxi Gas Group New Energy Development Co.,Ltd,Xi'an 710016,China

出　　处：《CSEE Journal of Power and Energy Systems》2022年第4期1039-1047,共9页中国电机工程学会电力与能源系统学报（英文）

基　　金：supported by the Research Fund of the State Key Laboratory of Eco-hydraulics in Northwest Arid Region,Xi'an University of Technology(Grant No.2019KJCXTD-5);the Natural Science Basic Research Program of Shaanxi(Grant No.2019JLZ-15);the Key Research and Development Plan of Shaanxi Province(Grant No.2018-ZDCXL-GY-10-04).

摘　　要：Large-scale new energy pressures on the grids bring challenges to power system's security and stability.In order to optimize the user's electricity consumption behavior and ease pressure,which is caused by new energy on the grid,this paper proposes a time-of-use price model that takes wind power uncertainty into account.First,the interval prediction method is used to predict wind power.Then typical wind power scenes are selected by random sampling and bisecting the K-means algorithm.On this basis,integer programming is used to divide the peak-valley period of the multi-scenes load.Finally,under the condition of many factors such as user response based on consumer psychology,user electricity charge and power consumption,this paper takes the peak-valley difference of equivalent net load and the user dissatisfaction degree as the goal,and using the NSGA-II multi-objective optimization algorithm,evaluates the Pareto solution set to obtain the optimal solution.In order to test the validity of the model proposed in this paper,we apply it to an industrial user and wind farms in Yan'an city,China.The results show that the model can effectively ensure the user's electrical comfort while achieving the role of peak shaving and valley flling.

关 键 词：Bisecting K-means algorithm interval prediction integer programming NSGA-II algorithm peakvalley difference time-of-use price user dissatisfaction wind power uncertainty 

分 类 号：TM614[电气工程—电力系统及自动化]