IEEE WF-IoT Session: Controlling Electric Vehicle Charging in the Smart Grid
Thomas Kunz, Carleton University, Canada; Wang Xiang, Carleton University, Canada; Marc St-Hilaire, Carleton University, Canada
Efficient scheduling and coordination algorithms controlling Electric Vehicle (EV) charging operations can potentially lead to energy consumption reduction and/or load balancing, in conjunction with different electricity pricing methods used in smart grid programs. In order to easily implement different algorithms and evaluate and compare their efficiency against other ideas, a flexible simulation framework is proposed. This simulation framework focuses on demand-side residential energy consumption coordination in response to different pricing methods. It is equipped with an appliance consumption library using realistic values to closely represent the average usage of different types of appliances including EVs. In this paper, a prototype program is developed and used to analyze EV charging and coordination algorithm impacts. The simulation run from the program gives a complete picture of the households' power consumption profile. Some results, analysis, and implications are presented in this paper demonstrating how the proposed tool can be used to study the impact of policy decisions.