Stability Improvement of Sulselrabar System With Integrated Wind Power Plant Using Multi-Band PSS3C Based Mayfly Optimization Algorithm

The introduction of additional controllers is essential in modern electric power systems to enhance their stability, particularly during disturbances. One effective method is the implementation of power system stabilizers (PSS). However, precise coordination of PSS equipment is necessary to determin...

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Vydáno v:IEEE access Ročník 12; s. 76707 - 76734
Hlavní autoři: Ruswandi Djalal, Muhammad, Robandi, Imam, Almas Prakasa, Mohamad
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Artificial intelligence
Coordination
Damping
Damping ratio
Eigenvalues
Electric potential
Electric power systems
Generators
mayfly optimization algorithm
multi-band PSS3C
Numerical stability
Optimization
Optimization algorithms
Optimization methods
Oscillators
Parameters
Performance evaluation
Power plants
Power system stability
Rotors
Stability
Stability analysis
Sulselrabar
System effectiveness
Time domain analysis
Voltage
Wind power
Wind power generation
wind power plant
ISSN:2169-3536, 2169-3536
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Shrnutí:The introduction of additional controllers is essential in modern electric power systems to enhance their stability, particularly during disturbances. One effective method is the implementation of power system stabilizers (PSS). However, precise coordination of PSS equipment is necessary to determine the optimal locations and parameters. This study focuses on the optimal analysis of Multi-Band PSS3C (MB-PSS3C) coordination in integrated Wind Power Plant (WPP) systems in South, Southeast, and West Sulawesi (Sulselrabar). An artificial intelligence approach, utilizing the Mayfly Optimization Algorithm (MOA), is suggested for optimizing both the location and parameters of the PSS. Comparative investigations were conducted to assess the efficacy of MB-PSS3C in comparison with SB-PSS1A and MB-PSS2B, based on previous research. The performance analysis employed the time domain simulation method, reviewing the speed deviation response, field voltage response, PSS output voltage response, and rotor angle response for each generator. Eigenvalue analysis was performed for each control scheme. Load changes were applied to generators 1 (BAKARU) and 11 (WPP SIDRAP) to evaluate the performance of the system. The application of the MOA-based MB-PSS3C results in an increased damping ratio, improved speed response, and a more optimal rotor angle. MB-PSS3C provides a larger additional damping signal to the generator exciter, as indicated by the increase in the field voltage on the generator.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2024.3406434