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Flow control in a small Francis turbine by system identification and fuzzy adaptation of PID and deadband controllers

Author

Listed:
  • Vinod, J.
  • Sarkar, Bikash K.
  • Sanyal, Dipankar

Abstract

The ever-escalating power-demand together with depletion of fossil-fuel reserve and increasing-thrust on using climate-friendly system drive the transition to higher use of sustainable-green-energy. There is an immense need of harnessing hydraulic power from runaway-streams in hill-areas from small-hydropower-installations. A laboratory-scale system with Francis-turbine has been set-up with low-cost easily-maintainable electrohydraulic-actuation system for controlling the opening of the inlet-guide-vanes. The actuation system has a proportional-valve and cylinder. Deadband-nonlinearities due to the valve-overlap and cylinder-friction in this system along with large-disturbances in both the connected-load and the upstream-water head have been tackled by appropriate system-modelling supplemented by identification of the model-parameters. These parameters have been estimated by carrying-out steady-state-performance test at a rated-speed of the turbine combined with simulation of the model. A real-coded-genetic-algorithm has been used for parameter-updating the aiming minimum deviation between the experimental-variation of the turbine-efficiency against discharge and the evolving simulation-prediction. This model has been utilized for extracting the demand of the guide-vane-actuation-system in the face of head and power-disturbances. A controller with fuzzy-tuned PI-gains and a nonlinear deadband function has been proposed. Experimental-results demonstrate successful-tackling of large-power disturbances by the containment of the maximum-departure of the turbine speed in the open-loop from the rated-value to only 0.156%.

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  • Vinod, J. & Sarkar, Bikash K. & Sanyal, Dipankar, 2022. "Flow control in a small Francis turbine by system identification and fuzzy adaptation of PID and deadband controllers," Renewable Energy, Elsevier, vol. 201(P2), pages 87-99.
  • Handle: RePEc:eee:renene:v:201:y:2022:i:p2:p:87-99
    DOI: 10.1016/j.renene.2022.11.039
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