Journal of Communications and Networks

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Comparison of Intelligent Charging Algorithms for Electric Vehicles to Reduce Peak Load and Demand Variability in a Distribution Grid

  • Received : 2012.05.15
  • Published : 2012.12.31
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Abstract

A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage.

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References

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