Online mechanism design for electric vehicle charging
Gerding, Enrico H., Robu, Valentin, Stein, Sebastian, Parkes, David C., Rogers, Alex and Jennings, Nickolas R. (2011) Online mechanism design for electric vehicle charging. At Tenth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2011), Taipei, TW, 02 - 06 May 2011. , 1-8.
- Published Version
The rapid increase in the popularity of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) is expected to place a considerable strain on the existing electricity grids, due to the high charging rates these vehicles require. In many places, the limited capacity of the local electricity distribution network will be exceeded if many such vehicles are plugged in and left to charge their batteries simultaneously. Thus, it will become increasingly important to schedule the charging of these vehicles, taking into account the vehicle owners’ preferences, and the local constraints on the network. In this paper, we address this setting using online mechanism design and develop a mechanism that incentivises agents (representing vehicle owners) to truthfully reveal their preferences, as well as when the vehicle is available for charging. Existing related online mechanisms assume that agent preferences can be described by a single parameter. However, this is not appropriate for our setting since agents are interested in acquiring multiple units of electricity and can have different preferences for these units, depending on factors such as their expected travel distance. To this end, we extend the state of the art in online mechanism design to multi-valued domains, where agents have non-increasing marginal valuations for each subsequent unit of electricity. Interestingly, we show that, in these domains, the mechanism occasionally requires leaving electricity unallocated to ensure truthfulness. We formally prove that the proposed mechanism is dominant-strategy incentive compatible, and furthermore, we empirically evaluate our mechanism using data from a real-world trial of electric vehicles in the UK. We show that our approach outperforms any fixed price mechanism in terms of allocation efficiency, while performing only slightly worse than a standard scheduling heuristic, which assumes non-strategic agents.
|Item Type:||Conference or Workshop Item (Speech)|
|Keywords:||electric vehicle, mechanism design, pricing|
|Subjects:||T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TL Motor vehicles. Aeronautics. Astronautics
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Agents, Interactions & Complexity
|Date Deposited:||16 Jan 2011 15:13|
|Last Modified:||14 Apr 2014 11:34|
EUROCORES LogiCCC (collaboration led by Dr. Edith Elkind): Computational Foundations of Social Choice.
Funded by: ESRC (RES-000-22-2731)
Led by: Edith Elkind
Led by: Enrico Harm Gerding
1 September 2008 to 29 February 2012
|Further Information:||Google Scholar|
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