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Online mechanism design for electric vehicle charging

Online mechanism design for electric vehicle charging
Online mechanism design for electric vehicle charging
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.
electric vehicle, mechanism design, pricing
811-818
Gerding, Enrico H.
d9e92ee5-1a8c-4467-a689-8363e7743362
Robu, Valentin
36b30550-208e-48d4-8f0e-8ff6976cf566
Stein, Sebastian
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
Parkes, David C.
3c873bcd-d181-4d6f-9347-ac345399f8d3
Rogers, Alex
f9130bc6-da32-474e-9fab-6c6cb8077fdc
Jennings, Nicholas R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Gerding, Enrico H.
d9e92ee5-1a8c-4467-a689-8363e7743362
Robu, Valentin
36b30550-208e-48d4-8f0e-8ff6976cf566
Stein, Sebastian
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
Parkes, David C.
3c873bcd-d181-4d6f-9347-ac345399f8d3
Rogers, Alex
f9130bc6-da32-474e-9fab-6c6cb8077fdc
Jennings, Nicholas R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Gerding, Enrico H., Robu, Valentin, Stein, Sebastian, Parkes, David C., Rogers, Alex and Jennings, Nicholas R. (2011) Online mechanism design for electric vehicle charging. Tenth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2011), Taipei. 02 - 06 May 2011. pp. 811-818 .

Record type: Conference or Workshop Item (Other)

Abstract

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.

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More information

Published date: May 2011
Venue - Dates: Tenth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2011), Taipei, 2011-05-02 - 2011-05-06
Keywords: electric vehicle, mechanism design, pricing
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 271907
URI: https://eprints.soton.ac.uk/id/eprint/271907
PURE UUID: e108918f-1ddc-49df-acec-bf9e8f05ca3c
ORCID for Enrico H. Gerding: ORCID iD orcid.org/0000-0001-7200-552X

Catalogue record

Date deposited: 16 Jan 2011 15:13
Last modified: 15 Aug 2019 00:43

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Contributors

Author: Enrico H. Gerding ORCID iD
Author: Valentin Robu
Author: Sebastian Stein
Author: David C. Parkes
Author: Alex Rogers
Author: Nicholas R. Jennings

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