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A novel intelligent method to increase accuracy of hybrid photovoltaic-wind system-based MPPT and pitch angle controller

  • Optimization
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Abstract

The main aim of this paper is the optimal power extraction based on an intelligent structure. It is implemented through fuzzy gain scheduling of PID (FGS-PID) controller in combination with the radial basis function network sliding mode (RBFNSM) for controlling a grid-connected hybrid generating system. A wind turbine (WT) based on the permanent magnet synchronous generator (PMSG) and a photovoltaic (PV) is considered for this study. FGS-PID controller equipped with scaling factors (SF) for the input signals of FGS are used to reach MPPT for the PV system. In order to regulate the member functions (MFs) of FGS, the fuzzy logic controller (FLC) and developed farmland fertility optimization (IFFO) algorithm are used. Moreover, the pitch angle control is applied for the WT. The pitch angle control of the WT is implemented by the RBFNSM to control the generated power and the speed at the nominal value. For protecting the wind turbine architecturally and escape catastrophic operation, this idea is implemented. MATLAB software is used to show the effectiveness of the proposed controller. The main advantages of the proposed method over other approaches are efficiency, fast and accurately tracking the highest generated power of the PV system.

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Acknowledgements

This work was supported by Foundation of State Key Laboratory of Public Big Data (No.2023004), National Natural Science Foundation of China (No.61862051), the Science and Technology Foundation of Guizhou Province (No. ZK[2022]549), the Natural Science Foundation of Education of Guizhou province (No. [2019]203, No. KY[2019]067), and the Funds of Qiannan Normal University for Nationalities (No.qnsy2019rc09).

Funding

This study was not funded any institution and organization.

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Authors and Affiliations

  1. School of Computer and Information, Qiannan Normal University for Nationalities, Duyun, 558000, Guizhou, China

    Tao Hai & Jincheng Zhou

  2. State Key Laboratory of Public Big Data, Guizhou University, Guiyang, 550025, Guizhou, China

    Tao Hai

  3. Institute for Big Data Analytics and Artificial Intelligence (IBDAAI), Universiti Teknologi MARA, 40450, Shah Alam, Selangor, Malaysia

    Tao Hai

  4. Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province, Duyun, 558000, China

    Jincheng Zhou

  5. Key Laboratory of Complex Systems and Intelligent Optimization of Qiannan, Duyun, 558000, China

    Jincheng Zhou

  6. Department of Electrical Engineering, Saveh Branch, Islamic Azad University, Saveh, Iran

    Sajjad Dadfar

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  1. Tao Hai
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  2. Jincheng Zhou
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  3. Sajjad Dadfar
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Correspondence to Jincheng Zhou or Sajjad Dadfar.

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Hai, T., Zhou, J. & Dadfar, S. A novel intelligent method to increase accuracy of hybrid photovoltaic-wind system-based MPPT and pitch angle controller. Soft Comput 27, 7401–7418 (2023). https://doi.org/10.1007/s00500-023-07977-5

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