Online Mechanism Design for Electric Vehicle Charging

DSpace/Manakin Repository

Online Mechanism Design for Electric Vehicle Charging

Citable link to this page


Title: Online Mechanism Design for Electric Vehicle Charging
Author: Gerding, Enrico H.; Robu, Valentin; Stein, Sebastian; Parkes, David C.; Rogers, Alex; Jennings, Nicholas R.

Note: Order does not necessarily reflect citation order of authors.

Citation: Gerding, Enrico H., Valentin Robu, Sebastian Stein, David C. Parkes, Alex Rogers, and Nicholas R. Jennings. 2011. Online mechanism design for electric vehicle charging. In Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011): May, 2-6, 2011, Taipei, Taiwan, ed. Kagan Tumer, Pinar Yolum, Liz Sonenberg, and Peter Stone, 811-818. Richland, South Carolina: International Foundation for Autonomous Agents and Multiagent Systems.
Full Text & Related Files:
Abstract: Plug-in hybrid electric vehicles are expected to place a considerable strain on local electricity distribution networks, requiring charging to be coordinated in order to accommodate capacity constraints. We design a novel online auction protocol for this problem, wherein vehicle owners use agents to bid for power and also state time windows in which a vehicle is available for charging. This is a multi-dimensional mechanism design domain, with owners having non-increasing marginal valuations for each subsequent unit of electricity. In our design, we couple a greedy allocation algorithm with the occasional "burning" of allocated power, leaving it unallocated, in order to adjust an allocation and achieve monotonicity and thus truthfulness. We consider two variations: burning at each time step or on-departure. Both mechanisms are evaluated in depth, using data from a real-world trial of electric vehicles in the UK to simulate system dynamics and valuations. The mechanisms provide higher allocative efficiency than a fixed price system, are almost competitive with a standard scheduling heuristic which assumes non-strategic agents, and can sustain a substantially larger number of vehicles at the same per-owner fuel cost saving than a simple random scheme.
Published Version:
Other Sources:
Terms of Use: This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at
Citable link to this page:
Downloads of this work:

Show full Dublin Core record

This item appears in the following Collection(s)


Search DASH

Advanced Search