Journal of Green Energy Research and Innovation
Quarterly

Applying Sliding Mode Control Along with Particle Swarm Algorithm in Order to Optimally Control the System Wind Turbines with Variable Speed

Document Type : Research article

Authors

Sasan Pirouzi 1
Ali Naderi 2

1 Islamic Azad University of Semmirom Branch, Semmirom, Iran.

2 Department of Engineering, Yazd University, Yazd, Iran.

https://doi.org/10.61186/jgeri.1.2.64
Abstract
The utilization of renewables is developing rapidly due to environmental issues and a lack of fuel fossils. In this regard, wind turbines, as a type of renewable energy source, have been widely adopted in the power system thanks to their higher power generation capacity. Numerous methods have been introduced so far to control wind turbines, which are essential in generating wind energy. The sliding mode control, because of its unique features like being resistant to external disturbances, dynamics unmodeled and uncertainty, the relative simplicity of the control law, a relatively small amount of calculations, and straightforward implementation, is amongst the most preferred control designs in this realm. In this study, the control strategy is based on a combination of sliding mode and particle swarm optimization and is applied to a wind turbine with a grid-connected squirrel cage induction generator. The proposed method maximizes the power output of the wind turbine by limiting small changes in the electromagnetic torque.­ The main goal of the suggested design is to reduce the squared error of the electromagnetic torque, rotor speed, and stator current.­ The sliding mode control for the wind turbine helps obtain optimal values for the parameters of the design. 

Graphical Abstract

Applying Sliding Mode Control Along with Particle Swarm Algorithm in Order to Optimally Control the System Wind Turbines with Variable Speed

Highlights

 

  • MPP tracking while observing the allowed range of duty cycle
  • Preserving the permissible range of ripples of various parameters
  • Extending the operating range of the variable-resistance method
  • Adopting the proposed method for PV energy management

 

Keywords

Wind turbine
Sliding mode control
Particle swarm algorithm

 

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The ethical issues, including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, redundancy, have been completely observed by the authors.

 

Credit Authorship Contribution Statement

Sasan Pirouzi: Conceptualization, Formal analysis, Project administration, Supervision, Validation, Roles/Writing - original draft. Ali Naderi: Conceptualization, Investigation, Methodology, Resources, Visualization, Writing - review & editing.

 

Bibliography

Sasan Pirouzi received a BSc degree in electrical engineering from the Technical and Vocational University, Mashhad, Iran, in 2012 and an MSc degree from the Isfahan University of Technology, Isfahan, Iran, in 2014, as well as a PhD from the Shiraz University of Technology (SUTECH), Shiraz, Iran, in 2017. His research interests are power system operation and planning, electric vehicles, DERs and the application of optimization methods in power systems.

Ali Naderi was born in Iran. He is currently a master's student in the field of electrical engineering at Yazd University. His special interests are operation and planning of power systems.

 

Citation

S. Pirouzi, and A. Naderi, "Applying Sliding Mode Control Along with Particle Swarm Algorithm in Order to Optimally Control the System Wind Turbines with Variable Speed‎‎," Journal of Green Energy Research and Innovation, vol. 1, no. 2, pp. 64-80, 2024.

 
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Journal of Green Energy Research and Innovation
Volume 1, Issue 2
Spring 2024
Pages 64-80

  • Receive Date 02 February 2024
  • Revise Date 01 March 2024
  • Accept Date 06 March 2024
  • Publish Date 01 June 2024

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