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Optimal Combinatorial Electricity Markets

Optimal Combinatorial Electricity Markets
Optimal Combinatorial Electricity Markets
The deregulation of the electricity industry in many countries has created a number of marketplaces in which producers and consumers can operate in order to more effectively manage and meet their energy needs. To this end, this paper develops a new model for electricity retail where end-use customers choose their supplier from competing electricity retailers. The model is based on simultaneous reverse combinatorial auctions, designed as a second-price sealed-bid multi-item auction with supply function bidding. This model prevents strategic bidding and allows the auctioneer to maximise its payoff. Furthermore, we develop optimal single-item and multi-item algorithms for winner determination in such auctions that are significantly less complex than those currently available in the literature.
123-135
Penya, Y.K.
57659273-9acf-42ff-8667-9f8ff5aff22d
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Penya, Y.K.
57659273-9acf-42ff-8667-9f8ff5aff22d
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Penya, Y.K. and Jennings, N. R. (2008) Optimal Combinatorial Electricity Markets. International Journal of Web Intelligence & Agent Systems, 6 (2), 123-135.

Record type: Article

Abstract

The deregulation of the electricity industry in many countries has created a number of marketplaces in which producers and consumers can operate in order to more effectively manage and meet their energy needs. To this end, this paper develops a new model for electricity retail where end-use customers choose their supplier from competing electricity retailers. The model is based on simultaneous reverse combinatorial auctions, designed as a second-price sealed-bid multi-item auction with supply function bidding. This model prevents strategic bidding and allows the auctioneer to maximise its payoff. Furthermore, we develop optimal single-item and multi-item algorithms for winner determination in such auctions that are significantly less complex than those currently available in the literature.

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More information

Published date: 2008
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 264665
URI: http://eprints.soton.ac.uk/id/eprint/264665
PURE UUID: 54be070d-6478-430a-b902-d6ce12ae3c72

Catalogue record

Date deposited: 10 Oct 2007
Last modified: 02 Dec 2019 21:04

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Contributors

Author: Y.K. Penya
Author: N. R. Jennings

University divisions

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