Title
Particle Swarm Optimization For Load Balancing In Green Smart Homes
Abstract
Particle Swarm Optimization (PSO) is a promising evolutionary algorithm, which has been used in a wide range of applications, due to its simple implementation, fast convergence, parallel behavior, and versatility in working with continuous and discrete domains. In this paper, we consider its application to the load balancing problem, in green smart homes. Specifically, an adapted version of the Binary PSO has been used to determine the optimal distribution of energy resources, across different green energy sources in a green smart home. The case study of interest considers the usage of solar and wind energy, as green energy sources for the green smart home. Results demonstrate the effectiveness of the algorithm, in terms of the optimal outcome (efficient distribution of energy resources), finding installation material surplus, and the execution speed of the algorithm. © 2011 IEEE.
Publication Date
8-29-2011
Publication Title
2011 IEEE Congress of Evolutionary Computation, CEC 2011
Number of Pages
715-720
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/CEC.2011.5949689
Copyright Status
Unknown
Socpus ID
80051976607 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/80051976607
STARS Citation
Lugo-Cordero, Hector M.; Fuentes-Rivera, Abigail; Guha, Ratan K.; and Ortiz-Rivera, Eduardo I., "Particle Swarm Optimization For Load Balancing In Green Smart Homes" (2011). Scopus Export 2010-2014. 2710.
https://stars.library.ucf.edu/scopus2010/2710