Modified Antipredatory Particle Swarm Optimization for Dynamic Economic Dispatch with Wind Power
Joint Authors
Shi, Liping
Chen, Kai
Han, Li
Wang, Shuhuan
Lu, Junjie
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-10-23
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
A modified antipredatory particle swarm optimization (MAPSO) algorithm with evasive adjustment behavior is proposed to solve the dynamic economic dispatch problem of wind power.
The algorithm adds the social avoidance inertia weight to the conventional antipredatory particle swarm optimization (APSO) speed update formula.
The size of inertia weight is determined by the distance between the global worst particle and other particles.
After normalizing the distance, the inertia weight is controlled within the ideal range by using the characteristics of sigmoid function and linear decreasing method, which improves the ability of particles to avoid the worst solution.
Then, according to the characteristics of the acceleration coefficient which can adjust the local and global searching ability of particles, acceleration coefficients of nonlinear change strategy is proposed to improve the searching ability of the algorithm.
Finally, the proposed algorithm is applied to several benchmark functions and power grid system models, and the results are compared with those reported using other algorithms, which prove the effectiveness and superiority of the proposed algorithm.
American Psychological Association (APA)
Chen, Kai& Han, Li& Wang, Shuhuan& Lu, Junjie& Shi, Liping. 2019. Modified Antipredatory Particle Swarm Optimization for Dynamic Economic Dispatch with Wind Power. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-17.
https://search.emarefa.net/detail/BIM-1196234
Modern Language Association (MLA)
Chen, Kai…[et al.]. Modified Antipredatory Particle Swarm Optimization for Dynamic Economic Dispatch with Wind Power. Mathematical Problems in Engineering No. 2019 (2019), pp.1-17.
https://search.emarefa.net/detail/BIM-1196234
American Medical Association (AMA)
Chen, Kai& Han, Li& Wang, Shuhuan& Lu, Junjie& Shi, Liping. Modified Antipredatory Particle Swarm Optimization for Dynamic Economic Dispatch with Wind Power. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-17.
https://search.emarefa.net/detail/BIM-1196234
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1196234