The time-of-use price optimization of electric vehicle charging and discharging based on clustering algorithm
Song Jian1, Li Mengjia2, Liu Nan3, Jing Peibo1, Guo Yaxin3
1. State Grid Shandong Dongying Electric Power Company, Dongying, Shandong 257091; 2. College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, Shandong 266590; 3. The limited company of Dongying Fangda about Electric Power Design and Planning, Dongying, Shandong 257091
Abstract：With the increase of electric vehicles, uncontrolled charging of electric vehicle will bring greater negative influence to the power system operation. At the same time, along with the electricity market reformation, the implementation of TOU price is the inevitable choice. Through a reasonable set of charging and discharging TOU price can guide the electric vehicle users. In this paper, private cars are taken as the research object. According to the user's charging duration and charging start time characteristics, the K-means clustering analysis is performed to obtain the user's daily charging rules. Therefore, an objective function for reducing grid fluctuations and the user's electricity cost is established. Finally, the optimal time-of-use price is solved by cuckoo search (CS) algorithm. Through the example of the actual load of a community, the scheduling strategy can effectively reduce user electricity cost and improve the operation of the power grid.
宋健, 李梦佳, 刘囡, 荆培波, 郭雅欣. 基于聚类算法的电动汽车充放电分时电价优化[J]. 电气技术, 2018, 19(8): 168-173.
Song Jian, Li Mengjia, Liu Nan, Jing Peibo, Guo Yaxin. The time-of-use price optimization of electric vehicle charging and discharging based on clustering algorithm. Electrical Engineering, 2018, 19(8): 168-173.
2018, Vol. 19 
