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Presenter: Kan Zhou
Supervisor: Dr. Lin Cai

Date: Wed, July 23, 2014
Time: 14:00:00 - 15:00:00
Place: EOW 430

ABSTRACT

Abstract:

Plug-in hybrid electric vehicle (PHEV), in addition to its environment-friendliness, brings both challenges (due to its high demand) and opportunities (thanks to the elasticity of its demand) to future smart grids. How to control users' elastic demand to reduce demand peaks and effectively use renewable energy despite its stochastic characteristic are key objects for smart grids, which also spark numerous research efforts. Existing solutions are either centralized which may not be scalable, or decentralized based on real time pricing (RTP) which may not be deployable immediately. In this paper, we introduce a new distributed random access approach for controlling PHEV charging process, which do not need complicated, centralized control and can be executed in real time. Different from the existing work, we use the history information rather than RTP to coordinate all the distributed smart agents who schedule the PHEV charging. Simulation results show that the proposed decentralized access algorithm is efficient and effective in reducing peaks caused by uncoordinated PHEV charging, and can provide automatic demand response to make the demand follow the change of renewable energy supply. Most importantly, the proposed algorithm is simple and scalable to implement.