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

• Type: Article in International Conference Proceedings Book
• Date: 2015

Authors

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

Conference proceedings International

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

Pages: 300-306

Indexing

ISI Web of Knowledge - 4 Citations

Scopus - 7 Citations

Scientific classification

CORDIS: Technological sciences > Engineering > Computer engineering

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7