Name
Title | ||
|---|---|---|
Comprehensive learning cuckoo search with chaos-lambda method for solving economic dispatch problems |
Abstract | ||
|---|---|---|
Economic dispatch (ED) is an important part in the economic operation of power systems. It is an NP-hard problem with multiple practical constraints. This paper proposes a novel approach that combines a swarm intelligence algorithm with a constraint-handling mechanism to solve the ED problem. First, we design a comprehensive learning cuckoo search algorithm with two strengthen strategies. A comprehensive learning strategy is designed to give the algorithm advanced learning ability in high-dimensional and multi-modal environment and thus enhance the search ability. A duplicate elimination strategy is utilized as an elite strategy to improve the evolving efficiency of the algorithm. Then, we propose a constraint-based population generation method named chaos-lambda method to reduce the searching complexity, and a solution repair method to repair unfeasible solutions that violate the constraints. The proposed approach is tested on 5 systems with different benchmarks and compared with the state-of-the-art algorithms. Our approach achieves the best performance on every test. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/s10489-020-01654-y | Applied Intelligence |
Keywords | DocType | Volume |
Economic dispatch, Swarm intelligence, Cuckoo search, Power systems | Journal | 50 |
Issue | ISSN | Citations |
9 | 0924-669X | 1 |
PageRank | References | Authors |
0.37 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhenyu Huang | 1 | 1 | 0.37 |
| Jian Zhao | 2 | 1 | 0.37 |
| Liang Qi | 3 | 156 | 27.14 |
| Zhengzhong Gao | 4 | 1 | 0.37 |
| Hua Duan | 5 | 110 | 19.58 |