Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
398192 | International Journal of Electrical Power & Energy Systems | 2016 | 8 Pages |
Abstract
In recent years, various heuristic optimization methods have been developed. Many of these methods are inspired by swarm behaviors in nature. In this paper, a new optimization algorithm namely Gravitational Search Algorithm (GSA) based on the law of gravity and mass interactions is illustrated for designing Static Synchronous Series Compensator (SSSC) for single and multimachine power systems. In the proposed algorithm, the searcher agents are a collection of masses which interact with each other based on the Newtonian gravity and the laws of motion. The proposed method has been compared with some well-known heuristic search methods. The obtained results confirm the high performance of the proposed method in tuning SSSC compared with Bacteria Foraging (BF) and Genetic Algorithm (GA). Moreover, the results are presented to demonstrate the effectiveness of the proposed controller to improve the power systems stability over a wide range of loading conditions.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
S.M. Abd Elazim, E.S. Ali,