Design of optimal multi-objective-based facts component with proportional-integral-derivative controller using swarm optimization approach
This study proposes a multi-objective-based swarm intelligence method to improve angle stability. An optimization operation with single objective function only improves the performance of one perspective and ignores the other. The combination of two objective functions which derived from real and im...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Accent Social and Welfare Society
2021
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/32369/1/Design%20of%20optimal%20multi-objective-based%20facts%20component.pdf http://umpir.ump.edu.my/id/eprint/32369/ http://dx.doi.org/10.19101/IJATEE.2020.762132 http://dx.doi.org/10.19101/IJATEE.2020.762132 |
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| Summary: | This study proposes a multi-objective-based swarm intelligence method to improve angle stability. An optimization operation with single objective function only improves the performance of one perspective and ignores the other. The combination of two objective functions which derived from real and imaginary components of eigenvalue are able to provide better performance beyond the optimization capabilities of single objective function. Tested using MATLAB, the simulation is performed using a single machine attached to the infinite bus (SMIB) system equipped with static var compensator (SVC) that attached with PID controller (SVC-PID). The objective of this experiment is to explore the excellent parameters in SVC-PID to produce a more stable system. In addition to the comparison of objective functions, this study also compares particle swarm optimization (PSO) capabilities with evolutionary programming (EP) and artificial immune system (AIS) techniques. |
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