Demand-side Management in Power Grids: An Ant Colony Optimization Approach

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2015

Autores

André Silva (Autor) FEUP; João Marinheiro (Autor) FEUP; Henrique Lopes Cardoso (Autor) FEUP; Eugénio Oliveira (Autor) FEUP

Ata de Conferência Internacional

Título: 2015 IEEE 18th International Conference on Computational Science and Engineering

Páginas: 300-306

Indexação

ISI Web of Knowledge - 4 Citações

Scopus - 7 Citações

Classificação Científica

CORDIS: Ciências Tecnológicas > Engenharia > Engenharia de computadores

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

Outras Informações

ID Authenticus: P-00K-AM9

DOI: 10.1109/cse.2015.31

Abstract (EN): As more and more fossil fuels are burned in order to keep up with the overgrowing demand for energy it is becoming increasingly necessary to look for alternative energy sources. Reducing peak-time energy demand is important to make the best use of renewable energies. In this paper we present an Ant Colony Optimization (ACO) based approach for the problem of scheduling tasks so as to minimize peak-times and cost. This approach is compared with an existing Genetic Algorithm (GA) based approach. ACO managed to obtain very similar results compared with GA, with the cost of the schedules being sometimes slightly better than the Genetic Algorithm approach, especially for shorter execution times. The ACO approach also proved to be more consistent in its results than the GA approach.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 7