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Application of multi-model control with fuzzy switching to a micro hydro-electrical power plant

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  • Salhi, Issam
  • Doubabi, Saïd
  • Essounbouli, Najib
  • Hamzaoui, Abdelaziz

Abstract

Modelling hydraulic turbine generating systems is not an easy task because they are non-linear and uncertain where the operating points are time varying. One way to overcome this problem is to use Takagi–Sugeno (TS) models, which offer the possibility to apply some tools from linear control theory, whereas those models are composed of linear models connected by a fuzzy activation function. This paper presents an approach to model and control a micro hydro power plant considered as a non-linear system using TS fuzzy systems. A TS fuzzy system with local models is used to obtain a global model of the studied plant. Then, to combine efficiency and simplicity of design, PI controllers are synthesised for each considered operating point to be used as conclusion of an electrical load TS Fuzzy controller. The latter ensures the global stability and desired performance despite the change of operating point. The proposed approach (model and controller) is tested on a laboratory prototype, where the obtained results show their efficiency and their capability to ensure good performance despite the non-linear nature of the plant.

Suggested Citation

  • Salhi, Issam & Doubabi, Saïd & Essounbouli, Najib & Hamzaoui, Abdelaziz, 2010. "Application of multi-model control with fuzzy switching to a micro hydro-electrical power plant," Renewable Energy, Elsevier, vol. 35(9), pages 2071-2079.
    • Handle: RePEc:eee:renene:v:35:y:2010:i:9:p:2071-2079
    DOI: 10.1016/j.renene.2010.02.008
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    References listed on IDEAS

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    1. Kishor, Nand & Saini, R.P. & Singh, S.P., 2007. "A review on hydropower plant models and control," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(5), pages 776-796, June.
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    Cited by:

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    2. Chang Xu & Dianwei Qian, 2015. "Governor Design for a Hydropower Plant with an Upstream Surge Tank by GA-Based Fuzzy Reduced-Order Sliding Mode," Energies, MDPI, vol. 8(12), pages 1-16, November.
    3. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
    4. Laghari, J.A. & Mokhlis, H. & Bakar, A.H.A. & Mohammad, Hasmaini, 2013. "A comprehensive overview of new designs in the hydraulic, electrical equipments and controllers of mini hydro power plants making it cost effective technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 279-293.
    5. Zoukit, Ahmed & El Ferouali, Hicham & Salhi, Issam & Doubabi, Said & Abdenouri, Naji, 2019. "Takagi Sugeno fuzzy modeling applied to an indirect solar dryer operated in both natural and forced convection," Renewable Energy, Elsevier, vol. 133(C), pages 849-860.
    6. Leonardo Peña-Pupo & Herminio Martínez-García & Encarna García-Vílchez & Ernesto Y. Fariñas-Wong & José R. Núñez-Álvarez, 2021. "Combined Method of Flow-Reduced Dump Load for Frequency Control of an Autonomous Micro-Hydropower in AC Microgrids," Energies, MDPI, vol. 14(23), pages 1-17, December.

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