The deregulation of the energy industry has created marketplaces in which producers and consumers can operate in order to more effectively. This book develops a new model for electricity retail where customers may choose their supplier. It is based on simultaneous reverse combinatorial auctions, designed as a second-price sealed-bid multi-item auction with supply function bidding. This mechanism prevents strategic bidding and allows the auctioneer to maximise its pay-off. 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. Nevertheless, the consumption of the energy of each singular auctioneer has to be adapted to the submitted bids to maximise the pay-off. Thus, this work models the constellation of energy consumers as a distributed constraint opti-misation problem (dCOP). In order to overcome the specific domain demands, this book presents a novel optimal dCOP algorithm called COBB (Constraint Optimisation By Broadcasting), and adapts state-of-the-art counterparts. Empirical comparisons show that COBB clearly outperforms all of them.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.; 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. Seller Inventory # 9783639013269
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Taschenbuch. Condition: Neu. Optimal Algorithms for Energy Markets | Allocation and Scheduling of Demand in Deregulated Energy Markets | Yoseba Peña Landaburu | Taschenbuch | Kartoniert / Broschiert | Englisch | 2013 | VDM Verlag Dr. Müller | EAN 9783639013269 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu. Seller Inventory # 105623113
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