Design of a power scheduler based on the heuristic for preemptive appliances
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
Two-sided online markets for electric vehicle charging
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Intention-aware routing to minimise delays at electric vehicle charging stations
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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This paper proposes an efficient charging scheduler for electric vehicles and measures its performance, aiming at reducing peak power consumption while satisfying the diverse constraints specified in each charging request. Upon the arrival of a charging request via the underlying vehicle network, the scheduler builds the feasible schedule based on the activation time, the deadline, and the power load profile of each charging task, which is practically nonpreemptive. During the search space expansion of a backtracking algorithm, each step checks the constraint imposed on peak load, completion time, number of chargers, and precedence relation between tasks to prune unnecessary branches. The performance measurement result obtained from the prototype implementation reveals that the proposed scheme reduces the execution time by 80 %, achieves the peak load reduction by 11 %, and improves the schedulability by 5 %, compared with uncoordinated and list scheduling schemes for the given parameter set.