Data Compression and Reconstruction for EV Charging Stations Based on Principal Component Analysis

被引：0
|
作者：
Zhang, Qiang [1 ]
Liu, Liping [1 ]
Liu, Chao [1 ]
机构：
[1] Tianjin Univ, Sch Elect Engn & Automat, Tianjin 300072, Peoples R China
来源：
MECHATRONICS ENGINEERING, COMPUTING AND INFORMATION TECHNOLOGY | 2014年 / 556-562卷
关键词：
Data Compression; Principal Component Analysis; Electric Vehicles; Smart Grid;
D O I：
10.4028/www.scientific.net/AMM.556-562.4317
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
As a zero-emission mode of transportation, an increasing number of Electric Vehicles (EV) have come into use in our daily lives. The EV charging station is an important component of the Smart Grid which is now facing the challenges of big data. This paper presents a data compression and reconstruction method based on the technique of Principal Component Analysis (PCA). The data reconstruction error Normalized Absolute Percent Error (NAPE) is taken into consideration to balance the compression ratio and data reconstruction quality. By using the simulated data, the effectiveness of data compression and reconstruction for EV charging stations are verified.
引用
收藏
页码：4317 / 4320
页数：4
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