LAPSE:2023.18759
Published Article

LAPSE:2023.18759
Reduction of Total Harmonic Distortion of Wind Turbine Active Power Using Blade Angle Adaptive PI Controller
March 8, 2023
Abstract
Power quality can have a large detrimental effect on industrial processes and the commercial sector. Thus, this paper proposes a new technique to improve the power quality of electric power systems. This technique relies on auto-adjusting of the blade angle to mitigate the harmonics in wind generator active power. A new adaptive PI blade-angle controller is applied in this technique to reduce the total harmonic distortion (THD) of the output power. The parameters of the adaptive PI controller are initialized by using the Harmony Search algorithm (HSA), hybrid Harmony Search optimization and Equilibrium optimization (EO), and hybrid Harmony Search optimization and Teaching learning-based optimization (TLBO). The execution of the optimization algorithms relies mainly on the optimization objective function. Two optimization objective functions are mathematically modeled and compared to enhance the power quality. The first one is to minimize the sum square of error, while the second objective is to minimize the THD. Many case studies are applied with various wind-speed profiles under normal and faulty conditions. Results show the superiority of HSA hybrid EO algorithm with the second objective functions through reducing the harmonics and enhancing the power quality. Moreover, laboratory studies are applied to investigate the effect of the blade-angle variations on the extracted active power.
Power quality can have a large detrimental effect on industrial processes and the commercial sector. Thus, this paper proposes a new technique to improve the power quality of electric power systems. This technique relies on auto-adjusting of the blade angle to mitigate the harmonics in wind generator active power. A new adaptive PI blade-angle controller is applied in this technique to reduce the total harmonic distortion (THD) of the output power. The parameters of the adaptive PI controller are initialized by using the Harmony Search algorithm (HSA), hybrid Harmony Search optimization and Equilibrium optimization (EO), and hybrid Harmony Search optimization and Teaching learning-based optimization (TLBO). The execution of the optimization algorithms relies mainly on the optimization objective function. Two optimization objective functions are mathematically modeled and compared to enhance the power quality. The first one is to minimize the sum square of error, while the second objective is to minimize the THD. Many case studies are applied with various wind-speed profiles under normal and faulty conditions. Results show the superiority of HSA hybrid EO algorithm with the second objective functions through reducing the harmonics and enhancing the power quality. Moreover, laboratory studies are applied to investigate the effect of the blade-angle variations on the extracted active power.
Record ID
Keywords
adaptive PI, equilibrium optimization, Harmony Search algorithm, PID controller, power quality, total harmonic distortion, wind turbine
Subject
Suggested Citation
Shawqran AM, El-Marhomy A, Sameh MA, Attia MA. Reduction of Total Harmonic Distortion of Wind Turbine Active Power Using Blade Angle Adaptive PI Controller. (2023). LAPSE:2023.18759
Author Affiliations
Shawqran AM: Physics and Engineering Mathematics Department, Faculty of Engineering, Ain Shams University, Cairo 11835, Egypt
El-Marhomy A: Physics and Engineering Mathematics Department, Faculty of Engineering, Ain Shams University, Cairo 11835, Egypt
Sameh MA: Electrical Engineering Department, Faculty of Engineering, Future University in Egypt, Cairo 11835, Egypt [ORCID]
Attia MA: Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11835, Egypt [ORCID]
El-Marhomy A: Physics and Engineering Mathematics Department, Faculty of Engineering, Ain Shams University, Cairo 11835, Egypt
Sameh MA: Electrical Engineering Department, Faculty of Engineering, Future University in Egypt, Cairo 11835, Egypt [ORCID]
Attia MA: Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11835, Egypt [ORCID]
Journal Name
Energies
Volume
14
Issue
20
First Page
6798
Year
2021
Publication Date
2021-10-18
ISSN
1996-1073
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Original Submission
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PII: en14206798, Publication Type: Journal Article
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LAPSE:2023.18759
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https://doi.org/10.3390/en14206798
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Mar 8, 2023
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