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

Qiang Zhang; Li Ping Liu; Chao Liu

doi:10.4028/www.scientific.net/AMM.556-562.4317

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562Data Compression and Reconstruction for EV...

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

Abstract:

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.

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Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

4317-4320

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.4317

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Online since:

May 2014

Authors:

Qiang Zhang*, Li Ping Liu, Chao Liu

Keywords:

Data Compression, Electric Vehicle (EV), Principal Component Analysis (PCA), Smart Grid (SG)

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* - Corresponding Author

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