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

26Citations
Citations of this article
33Readers
Mendeley users who have this article in their library.
Get full text

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.

Cite

CITATION STYLE

APA

Katsigiannis, Y. A., Georgilakis, P. S., & Karapidakis, E. S. (2010). Genetic algorithm solution to optimal sizing problem of small autonomous hybrid power systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6040 LNAI, pp. 327–332). https://doi.org/10.1007/978-3-642-12842-4_38

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free