Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1732541 | Energy | 2014 | 16 Pages |
Abstract
This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.
Keywords
Related Topics
Physical Sciences and Engineering
Energy
Energy (General)
Authors
Tiago Sousa, Zita Vale, Joao Paulo Carvalho, Tiago Pinto, Hugo Morais,