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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Abstract	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.
AbstractList	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. 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.
Author	Devi, G. Magesh, T. Thangavelu, Raja Jayaudhaya, J. Isabella, L. Annie
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SubjectTerms	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
Title	Optimal control of FOPID controllers for PMSG wind energy conversion system using golden eagle optimization algorithm
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