Research on Household Energy Control Method Based on Electric Vehicle

Xinyuan Zhang^1, , Yuqi Pang¹, Xunyu Liu¹ and Xiaotian Xu¹

¹School of NARI Electric & Automation engineering, Nanjing Normal University, Nanjing, China

Cite this paper

Xinyuan Zhang, Yuqi Pang, Xunyu Liu and Xiaotian Xu. Research on Household Energy Control Method Based on Electric Vehicle. American Journal of Electrical and Electronic Engineering. 2020; 8(3):80-83. doi: 10.12691/AJEEE-8-3-2

Abstract

With the development of the automobile industry, the extensive use of automobiles is a key factor in the global energy crisis and environmental pollution, and the clean and environmentally friendly characteristics of electric vehicles have become an ideal means to deal with these two major problems. Connecting household electric vehicles to the home will not only affect the distribution network, but also adversely affect the home electricity network. Therefore, it is necessary to connect electric vehicles to household charging load for quantitative analysis, so as to design energy control methods for electric vehicles to connect to households, and minimize the adverse effects of electric vehicles connected to household power grids. First of all, this article analyzes the uncertainty of electric vehicle access to the grid. After considering the random characteristics of electric vehicle charging load, an electric vehicle charging load model is built based on Monte Carlo simulation. Secondly, according to the electric vehicle charging load power curve obtained by the above method, combined with the daily load probability model of the grid, a household electricity model is established. Finally, based on the Particle Swarm Optimization(PSO), a family energy control method is proposed, and the optimization goal is to minimize the daily load fluctuation of the family, so as to minimize the impact of electric vehicles connected to the grid.

Keywords

electric vehicle charging, household energy control, Monte Carlo Method, PSO

Copyright

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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