Pattern recognition of electric vehicle charging and discharging based on the closeness degree

DOI

10.2991/emcpe-16.2016.106How to use a DOI?

Keywords

closeness degree, electric vehicle, non intrusive, smart meter, pattern recognition

Abstract

In the process of the intelligent network informatization, automation, and intelligent constantly improving, the requirements of power system for the transparency of the demand side are also getting higher and higher. Real-time and accurate load equipment identification for planning, load forecasting and price adjustment of power system is very important. Electric vehicles has been rapid development in recent years. Because of the characteristics of its battery charging storage, it can be a good part of "cut peak fill in the valley" in the power system. Based on data provided by the smart meters, the electric vehicle charging and discharging characteristics has been analyzed systematically. Conventional electric vehicle charging and discharging transient and steady state parameters as the basic template is used to design load identification method of electric vehicle charging and discharging based on non intrusive.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xi Chen
PY  - 2016/08
DA  - 2016/08
TI  - Pattern recognition of electric vehicle charging and discharging based on the closeness degree
BT  - Proceedings of the 2016 5th International Conference on Environment, Materials, Chemistry and Power Electronics
PB  - Atlantis Press
SP  - 330
EP  - 333
SN  - 2352-5401
UR  - https://doi.org/10.2991/emcpe-16.2016.106
DO  - 10.2991/emcpe-16.2016.106
ID  - Chen2016/08
ER  -