1.School of Economics and Management, North China Electric Power University, Beijing 102206, China;2.Zhejiang Zheneng Energy Service Co., Ltd., Hangzhou 310002, China;3.Huadian Electric Power Research Institute Co., Ltd., Hangzhou 310030, China;4.Economic Research Institute of State Grid Zhejiang Electricity Power Co., Ltd., Hangzhou 310016, China;5.Hangzhou Power Supply Company of State Grid Zhejiang Electricity Power Co., Ltd., Hangzhou 310009, China
In the background of Energy Internet, park operators firstly use distributed generators internally to meet the park electricity demand, and then exchange unbalanced energy externally. By formulating differentiated time-of-use (TOU) price packages, park operators can develop the demand response potential of park users, which can promote the local consumption of distributed generators and optimize the load exchange inside and outside the park. In this regard, a TOU pricing method for parks is proposed. Firstly, considering characteristics of electricity load and demand response, user groups in the park are clustered based on spectral clustering algorithm. Secondly, according to electricity load characteristics of user groups in the park, TOU periods are calculated based on k-means clustering algorithm. Finally, differentiated TOU price packages for different user groups in the park are formulated by constructing TOU pricing optimization model. According to the analysis of case examples, formulating TOU price in the park based on this method can effectively improve the local consumption rate and comprehensive utilization efficiency of the distributed generator in the park, as well as the friendliness with the external power grid and overall economy.
This work is supported by National Social Science Foundation of China (No. 19ZDA081) and Key Projects of Philosophy and Social Sciences Research, Ministry of Education (No. 18JZD032).
|||LIU Dunnan, XU Erfeng, LIU Mingguang, et al. TOU Pricing Method for Park Considering Local Consumption of Distributed Generator[J]. Automation of Electric Power Systems,2020,44(20):19-28. DOI:10.7500/AEPS20200123004|