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An adaptive control scheme for biomass-based diesel–wind system

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  • Jurado, Francisco
  • Saenz, José R.

Abstract

Control of autonomous diesel–wind systems is difficult because of time-varying dynamical properties, most of them as a result of plant non-stationary, non-linearity and random disturbances. In this paper, the system is composed of a pitch controlled wind turbine with an induction generator connected to an ac bus bar in parallel with a diesel generator set having a synchronous generator. A power plant can generate electric power using biomass from the olive tree in Spain. To have optimal response under disturbances, adaptive schemes appear to be a particularly attractive choice. The recursive least squares method and minimum-variance control algorithm is implemented to design the controller. This paper considers the application of an adaptive control methodology that allows the controller to automatically adjust to changing process variables and thereby provide uniform response over a wide range of operating conditions.

Suggested Citation

  • Jurado, Francisco & Saenz, José R., 2003. "An adaptive control scheme for biomass-based diesel–wind system," Renewable Energy, Elsevier, vol. 28(1), pages 45-57.
    • Handle: RePEc:eee:renene:v:28:y:2003:i:1:p:45-57
    DOI: 10.1016/S0960-1481(02)00012-5
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    References listed on IDEAS

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    1. Papathanassiou, Stavros A & Papadopoulos, Michael P, 2001. "Dynamic characteristics of autonomous wind–diesel systems," Renewable Energy, Elsevier, vol. 23(2), pages 293-311.
    2. Sfetsos, A., 2000. "A comparison of various forecasting techniques applied to mean hourly wind speed time series," Renewable Energy, Elsevier, vol. 21(1), pages 23-35.
    3. Tanaka, T. & Toumiya, T. & Suzuki, T., 1997. "Output control by hill-climbing method for a small scale wind power generating system," Renewable Energy, Elsevier, vol. 12(4), pages 387-400.
    4. Jurado, Francisco & Saenz, José R, 2002. "Neuro-fuzzy control for autonomous wind–diesel systems using biomass," Renewable Energy, Elsevier, vol. 27(1), pages 39-56.
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    Cited by:

    1. Deshmukh, M.K. & Deshmukh, S.S., 2008. "Modeling of hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(1), pages 235-249, January.

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