Genetic algorithm solution to optimal sizing problem of small autonomous hybrid power systems

Katsigiannis, YA; Georgilakis, PS; Karapidakis, ES

dc.contributor.author	Katsigiannis, YA	en
dc.contributor.author	Georgilakis, PS	en
dc.contributor.author	Karapidakis, ES	en
dc.date.accessioned	2014-03-01T02:46:48Z
dc.date.available	2014-03-01T02:46:48Z
dc.date.issued	2010	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32866
dc.subject	Combinatorial optimization	en
dc.subject	Genetic algorithms	en
dc.subject	Metaheuristics	en
dc.subject	Renewable energy sources	en
dc.subject	Small autonomous hybrid power systems	en
dc.subject.other	Algorithm solution	en
dc.subject.other	Binary genetic algorithm	en
dc.subject.other	Computational time	en
dc.subject.other	Exhaustive enumeration	en
dc.subject.other	Hybrid power systems	en
dc.subject.other	Key parameters	en
dc.subject.other	Meta heuristics	en
dc.subject.other	Natural selection	en
dc.subject.other	Optimal sizing	en
dc.subject.other	Optimization metaheuristic	en
dc.subject.other	Renewable energy source	en
dc.subject.other	Solution quality	en
dc.subject.other	Solution space	en
dc.subject.other	Artificial intelligence	en
dc.subject.other	Combinatorial optimization	en
dc.subject.other	Genetic algorithms	en
dc.subject.other	Heuristic algorithms	en
dc.subject.other	Renewable energy resources	en
dc.subject.other	Biology	en
dc.title	Genetic algorithm solution to optimal sizing problem of small autonomous hybrid power systems	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-642-12842-4_38	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-642-12842-4_38	en
heal.publicationDate	2010	en
heal.abstract	The optimal sizing of a small autonomous hybrid power system can be a very challenging task, due to the large number of design settings and the uncertainty in key parameters. This problem belongs to the category of combinatorial optimization, and its solution based on the traditional method of exhaustive enumeration can be proved extremely time-consuming. This paper proposes a binary genetic algorithm in order to solve the optimal sizing problem. Genetic algorithms are popular optimization metaheuristic techniques based on the principles of genetics and natural selection and evolution, and can be applied to discrete or continuous solution space problems. The obtained results prove the performance of the proposed methodology in terms of solution quality and computational time. © Springer-Verlag Berlin Heidelberg 2010.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-642-12842-4_38	en
dc.identifier.volume	6040 LNAI	en
dc.identifier.spage	327	en
dc.identifier.epage	332	en