Paper Info
Title
An Evaluation Strategy of Energy Storage Construction for Industrial Users Based on K-Means Clustering Algorithm
Abstract
Energy storage refers to a series of related technologies that achieve energy reserve and release by some ways when needed. Energy storage technology plays an important role in peak shaving and valley filling, improving the equipment utilization efficiency, enhancing the system safety and so on. It has great significances to realize the transformation of energy structure and the change of electricity production or consumption patterns for promoting the overall development of energy industry through the research of user-side energy storage technology. In this paper, we analyze the historical power consumption data of industrial users by K-Means clustering algorithm to design a user type automatic evaluation model, which can assist large industrial users to judge whether industrial users are suitable for energy storage construction or not, it can help enterprises save manpower and financial resources. In addition, we design a method to calculate the potential value of users, which can reflect the degree of suitability for equipping energy storage device. Simulation results show that the proposed model can correctly obtain the users’ typical load curve and power usage type through clustering historical power load data.
Year
DOI
Venue
2019
10.1109/ComComAp46287.2019.9018661
2019 Computing, Communications and IoT Applications (ComComAp)
Keywords
DocType
ISBN
K-Means clustering algorithm,Energy storage,Peak shaving and valley filling
Conference
978-1-7281-1974-8
Citations 
PageRank 
References 
0
0.34
2
Authors
8
Name
Order
Citations
PageRank
Yangyang Zhao1529.46
Boya Deng200.34
Hui Chen3513.63
Hualu Zhang400.34
Jie Shi500.34
Zhengwei Xu651.76
Xingyang Zhu700.34
Guangjie Han81890172.76