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Item Details
Title: COMPLEMENTARITY MODELING IN ENERGY MARKETS
By: Steven A. Gabriel, Antonio J. Conejo, J. David Fuller
Format: Hardback

List price: £99.99


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ISBN 10: 1441961224
ISBN 13: 9781441961228
Publisher: SPRINGER-VERLAG NEW YORK INC.
Pub. date: 29 May, 2011
Edition: 2013
Series: International Series in Operations Research & Management Science 180
Pages: 630
Description: In a straightforward and approachable manner, this book introduces complementarity models, and uses them to carry out an in-depth analysis of energy markets, including formulation issues and solution techniques.
Synopsis: This addition to the ISOR series introduces complementarity models in a straightforward and approachable manner and uses them to carry out an in-depth analysis of energy markets, including formulation issues and solution techniques. In a nutshell, complementarity models generalize: a. optimization problems via their Karush-Kuhn-Tucker conditions b. on-cooperative games in which each player may be solving a separate but related optimization problem with potentially overall system constraints (e.g., market-clearing conditions) c. conomic and engineering problems that aren't specifically derived from optimization problems (e.g., spatial price equilibria) d. roblems in which both primal and dual variables (prices) appear in the original formulation (e.g., The National Energy Modeling System (NEMS) or its precursor, PIES). As such, complementarity models are a very general and flexible modeling format. A natural question is why concentrate on energy markets for this complementarity approach? s it turns out, energy or other markets that have game theoretic aspects are best modeled by complementarity problems. The reason is that the traditional perfect competition approach no longer applies due to deregulation and restructuring of these markets and thus the corresponding optimization problems may no longer hold. Also, in some instances it is important in the original model formulation to involve both primal variables (e.g., production) as well as dual variables (e.g., market prices) for public and private sector energy planning. Traditional optimization problems can not directly handle this mixing of primal and dual variables but complementarity models can and this makes them all that more effective for decision-makers.
Illustrations: 76 Tables, black and white; XXVI, 630 p.
Publication: US
Imprint: Springer-Verlag New York Inc.
Returns: Returnable
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