Improved social spider optimization algorithm for optimal reactive power dispatch problem with different objectives

This paper proposes an improved social spider optimization (ISSO) for achieving different objectives of optimal reactive power dispatch (ORPD). The proposed ISSO method is developed by applying two modifications on new solution generation process. The proposed method uses only one modified equation...

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Bibliographic Details
Published in:Neural computing & applications 2020-05, Vol.32 (10), p.5919-5950
Main Authors: Nguyen, Thang Trung, Vo, Dieu Ngoc
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Computer simulation
Data Mining and Knowledge Discovery
Image Processing and Computer Vision
Methods
Optimization
Original Article
Parameters
Power dispatch
Probability and Statistics in Computer Science
Reactive power
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Summary:This paper proposes an improved social spider optimization (ISSO) for achieving different objectives of optimal reactive power dispatch (ORPD). The proposed ISSO method is developed by applying two modifications on new solution generation process. The proposed method uses only one modified equation for producing the first new solution generation and the second new solution generation while the standard SSO uses two equations for each process. The improvement in the proposed method is confirmed by solving benchmark optimization functions, IEEE 30-bus system and IEEE 118-bus system. Obtained results from ISSO are compared to those from other existing methods available in other studies together with other popular and state-of-the-art methods, which are implemented in the work. As compared to standard SSO for application to ORPD problem, ISSO can reduce the number of computation steps and one control parameter, and shorten simulation time. About the result comparisons with SSO and other remaining methods, ISSO can find more favorable solutions with higher quality and ISSO can stabilize solution search function with approximately all trial runs finding lower value of fitness. Furthermore, the strong search ability of ISSO is also indicated because it uses less value for control parameters. As a result, the proposed ISSO method can be a very effective optimization tool for dealing with the ORPD problem.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-019-04073-4