9781441961228-1441961224-Complementarity Modeling in Energy Markets (International Series in Operations Research & Management Science (180))

Complementarity Modeling in Energy Markets (International Series in Operations Research & Management Science (180))

ISBN-13: 9781441961228
ISBN-10: 1441961224
Edition: 2012
Author: Gabriel, Steven A., Conejo, Antonio J., Fuller, J. David, Hobbs, Benjamin F., Ruiz, Carlos
Publication date: 2012
Publisher: Springer
Format: Hardcover 656 pages
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Book details

ISBN-13: 9781441961228
ISBN-10: 1441961224
Edition: 2012
Author: Gabriel, Steven A., Conejo, Antonio J., Fuller, J. David, Hobbs, Benjamin F., Ruiz, Carlos
Publication date: 2012
Publisher: Springer
Format: Hardcover 656 pages

Summary

Acknowledged authors Gabriel, Steven A., Conejo, Antonio J., Fuller, J. David, Hobbs, Benjamin F., Ruiz, Carlos wrote Complementarity Modeling in Energy Markets (International Series in Operations Research & Management Science (180)) comprising 656 pages back in 2012. Textbook and eTextbook are published under ISBN 1441961224 and 9781441961228. Since then Complementarity Modeling in Energy Markets (International Series in Operations Research & Management Science (180)) textbook was available to sell back to BooksRun online for the top buyback price or rent at the marketplace.

Description

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.

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