Optimal control of FOPID controllers for PMSG wind energy conversion system using golden eagle optimization algorithm

This paper addresses the growing necessity for enhanced control strategies in wind energy conversion systems (WECS) to optimize the concert of permanent magnet synchronous generators (PMSG). The motivation for this research stems from the increasing reliance on renewable energy sources and the chall...

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Vydáno v:Electrical engineering Ročník 107; číslo 11; s. 14655 - 14670
Hlavní autoři: Jayaudhaya, J., Magesh, T., Devi, G., Isabella, L. Annie, Thangavelu, Raja
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2025
Springer Nature B.V
Témata:
Adaptability
Alternative energy sources
Control methods
Controllers
Design
Disturbances
Economics and Management
Efficiency
Electrical Engineering
Electrical Machines and Networks
Energy conversion
Energy Policy
Engineering
Genetic algorithms
Kalman filters
Load
Low voltage
Optimal control
Optimization algorithms
Optimization techniques
Original Paper
Parameters
Particle swarm optimization
Performance evaluation
Permanent magnets
Photovoltaic cells
Power Electronics
Proportional integral derivative
R&D
Renewable energy sources
Renewable resources
Research & development
Researchers
Synchronous machines
Systems stability
Turbines
Wind farms
Wind power
Golden eagle optimization
Fractional order proportional integral derivative
Maximum power point tracking
Permanent magnet synchronous generator
ISSN:0948-7921, 1432-0487
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Shrnutí:This paper addresses the growing necessity for enhanced control strategies in wind energy conversion systems (WECS) to optimize the concert of permanent magnet synchronous generators (PMSG). The motivation for this research stems from the increasing reliance on renewable energy sources and the challenges posed by grid disturbances, particularly during low voltage ride through (LVRT) events. The primary problem tackled is the inadequacy of traditional control methods, such as proportional integral (PI) and conventional optimization techniques, which often fail to provide satisfactory dynamic performance and stability in fluctuating wind conditions. To overcome these challenges, a novel fractional order proportional integral derivative (FOPID) controller is designed and its parameters are optimized using the golden eagle optimization algorithm (GEO). This methodology involves detailed simulations conducted in DIgSILENT/Matlab, focussing on transient and dynamic analyses to evaluate the controller's performance. The findings reveal that the GEO-FOPID controller exhibits a significant improvement in system response, with a rise time of 1.06 µs and a settling time of 8.02 µs, outperforming the particle swarm optimization (PSO) and genetic algorithm (GA) controllers by 75% and 85%, respectively. Notably, both the GEO-FOPID and PSO controllers achieved zero overshoot, enhancing the overall stability of the system during disturbances. This research contributes to the field by demonstrating the efficacy of FOPID controllers in WECS and highlights the technical novelty of utilizing the GEO algorithm for optimal parameter tuning. The results provide a promising avenue for future research to improve further the efficiency and reliability of wind energy systems in real-world applications.
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ISSN:0948-7921
1432-0487
DOI:10.1007/s00202-025-03285-3