Evolutionary Computation Methods for Fuzzy Decision Making on Load Dispatch Problems

Zhang, G; Gao, Y; Lu, J

Evolutionary Computation Methods for Fuzzy Decision Making on Load Dispatch Problems

Zhang, G

Gao, Y Lu, J

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Publisher:: Atlantis Press
Publication Type:: Chapter
Citation:: Computational Intelligence In Complex Decision Systems, 2010, 1st, pp. 301 - 323
Issue Date:: 2010-01

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Field	Value	Language
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.contributor.author	Gao, Y	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.contributor.editor	Da Ruan	en_US
dc.date.issued	2010-01	en_US
dc.identifier.citation	Computational Intelligence In Complex Decision Systems, 2010, 1st, pp. 301 - 323	en_US
dc.identifier.isbn	90-78677-27-9	en_US
dc.identifier.uri	http://hdl.handle.net/10453/14292
dc.description.abstract	This chapter introduces basic concepts relating to a day-ahead market in a power system. A load dispatch model considers a ramp rate and valve-point-loading effects. An environment/economic load dispatch model is presented to handle uncertainty factors. The model provides theoretical foundations for the research on operations and decision making in the electric power market. To solve load dispatch problems from day-ahead markets in power systems, a hybrid evolutionary computation method with a quasi-simplex technique, a weight point method for multi-objective programming, and a fuzzy-number-ranking-based optimization method for fuzzy multi-objective non-linear programming are developed.	en_US
dc.publisher	Atlantis Press	en_US
dc.relation.ispartof	Computational Intelligence In Complex Decision Systems	en_US
dc.title	Evolutionary Computation Methods for Fuzzy Decision Making on Load Dispatch Problems	en_US
dc.type	Chapter
utslib.location	Paris, France	en_US
utslib.for	080605 Decision Support and Group Support Systems	en_US
utslib.citation.edition	1st	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	open_access
pubs.consider-herdc	true	en_US
pubs.edition	1st	en_US
pubs.notes	OK	en_US
pubs.place-of-publication	Paris, France	en_US

Abstract:

This chapter introduces basic concepts relating to a day-ahead market in a power system. A load dispatch model considers a ramp rate and valve-point-loading effects. An environment/economic load dispatch model is presented to handle uncertainty factors. The model provides theoretical foundations for the research on operations and decision making in the electric power market. To solve load dispatch problems from day-ahead markets in power systems, a hybrid evolutionary computation method with a quasi-simplex technique, a weight point method for multi-objective programming, and a fuzzy-number-ranking-based optimization method for fuzzy multi-objective non-linear programming are developed.

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http://hdl.handle.net/10453/14292