A robust power system stabilizer for enhancement of stability in power system using adaptive fuzzy sliding mode control
This paper presents design of power system stabilizer (PSS) based on conventional fuzzy-PID and type-1 fuzzy controller for stability improvements in single as well as multimachine power system connected to infinite bus under different loading conditions. Again, fuzzy and integral sliding mode contr...
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| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/143801 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | This paper presents design of power system stabilizer (PSS) based on conventional fuzzy-PID and type-1 fuzzy controller for stability improvements in single as well as multimachine power system connected to infinite bus under different loading conditions. Again, fuzzy and integral sliding mode controllers (FSMC and I-SMC) are being incorporated with PSS into the power system to improve the stability performance. But, the presence of chattering in this controller may lead to low frequency oscillations of smaller magnitudes that can sustain to disturb the power transfer capability and the stability of the system. Therefore, to enhance the performance and efficiency of the power system, a novel adaptive fuzzy sliding mode controller with a robust sliding surface is designed to overcome the possible chattering due to system uncertainties and dynamics. In the proposed adaptive fuzzy sliding mode controller (AFSMC), the stability is ensured through Lyapunov analysis and synthesis test. In addition to the graphical simulation analysis, a quantitative stability approach and real-time test using OPAL-RT OP5600 is also carried out in order to augment the stability study. Further, stability test using eigen modes, root locus and Bode plots are presented to assess the stability performance of the proposed controller. Both the qualitative and quantitative analysis ensures better and robust performance of proposed controllers in comparison to the conventional fuzzy-PID and type-1 fuzzy controller. |
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