Optimal Algorithms for Energy Markets
Allocation and Scheduling of Demand in Deregulated Energy Markets
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The deregulation of the energy industry has createdmarketplaces in which producers and consumers canoperate in order to more effectively. This bookdevelops a new model for electricity retail wherecustomers may choose their supplier. It is based onsimultaneous reverse combinatorial auctions, designedas a second-price sealed-bid multi-item auction withsupply function bidding. This mechanism preventsstrategic bidding and allows the auctioneer tomaximise its pay-off. Furthermore, we develop optimalsingle-item and multi-item algorithms for winnerdetermination in such auctions that are significantly...
The deregulation of the energy industry has createdmarketplaces in which producers and consumers canoperate in order to more effectively. This bookdevelops a new model for electricity retail wherecustomers may choose their supplier. It is based onsimultaneous reverse combinatorial auctions, designedas a second-price sealed-bid multi-item auction withsupply function bidding. This mechanism preventsstrategic bidding and allows the auctioneer tomaximise its pay-off. Furthermore, we develop optimalsingle-item and multi-item algorithms for winnerdetermination in such auctions that are significantlyless complex than those currently available in theliterature. Nevertheless, the consumption of theenergy of each singular auctioneer has to be adaptedto the submitted bids to maximise the pay-off. Thus,this work models the constellation of energyconsumers as a distributed constraint optimisationproblem (dCOP). In order to overcome the specificdomain demands, this book presents a novel optimaldCOP algorithm called COBB (Constraint OptimisationBy Broadcasting), and adapts state-of-the-artcounterparts. Empirical comparisons show that COBBclearly outperforms all of them.
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