Sensing Cloud Optimization applied to a non-convex constrained economical dispatch

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2013

Autores

Pedro Fonte (Autor) Outra; Cláudio Monteiro (Autor) FEUP; Fernando Maciel Barbosa (Autor) FEUP

Ata de Conferência Internacional

Título: 39TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY (IECON 2013)

Páginas: 2163-2168

39th Annual Conference of the IEEE Industrial-Electronics-Society (IECON)

Vienna, AUSTRIA, NOV 10-14, 2013

Indexação

ISI Web of Knowledge - 3 Citações

Scopus - 3 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

CORDIS: Ciências Tecnológicas > Engenharia > Engenharia electrotécnica

Outras Informações

ID Authenticus: P-009-4SA

DOI: 10.1109/iecon.2013.6699466

Abstract (EN): In this paper it is intended to solve an Economical Dispatch (ED) problem with a new tool, named Sensing Cloud Optimization (SCO). It is a technique based on clouds of particles which allow a dynamic change in search space. It has appropriate heuristic characteristic to solve not convex, not differentiable and highly constrained optimisation problems. It is provided with a statistical analysis which determines the cloud's dimension with dynamic adjustments in search space in order to accelerate the convergence and to avoid to get trapped in local minima. Two case studies are presented in which SCO demonstrated good performances reaching lower cost values where compared with other techniques.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6