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Advanced Control to Improve the Ramp-Rate of a Gas Turbine: Optimization of Control Schedule

Author

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  • Young-Kwang Park

    (Graduate School, Inha University, 100 Inha-ro, Michuhol-Gu, Incheon 22212, Korea)

  • Seong-Won Moon

    (Graduate School, Inha University, 100 Inha-ro, Michuhol-Gu, Incheon 22212, Korea)

  • Tong-Seop Kim

    (Department of Mechanical Engineering, Inha University, 100 Inha-ro, Michuhol-Gu, Incheon 22212, Korea)

Abstract

As the proportion of power generation using renewable energy increases, it is important to improve the operational flexibility of gas turbines (GTs) for the stability of power grids. Increasing the ramp-rate of GTs is a general solution. However, a higher ramp-rate increases the turbine inlet temperature (TIT), its rate of change, and the fluctuation of the frequency of produced electricity, which are negative side effects. This study proposes a method to optimize the set-point schedule for a PID controller to improve the ramp-rate while decreasing the negative impacts. The set-point schedule was optimized for a 170-MW class GT using a genetic algorithm to minimize the difference between the value of the process variable and the set-point value of the conventional control. The advanced control reduced the fluctuation of the rotation speed by 20% at the reference ramp-rates (12 MW/min and 15 MW/min). The maximum TIT decreased by 6.3 °C, and its maximum rate of change decreased from 0.7 °C/s to 0.4 °C/s. The advantage of the advanced control becomes more marked as the ramp-rate increases. Even at a much higher ramp-rate (50 MW/min), the advanced control decreased the rotation speed fluctuation by 40% in comparison to the conventional control at the reference ramp-rate.

Suggested Citation

  • Young-Kwang Park & Seong-Won Moon & Tong-Seop Kim, 2021. "Advanced Control to Improve the Ramp-Rate of a Gas Turbine: Optimization of Control Schedule," Energies, MDPI, vol. 14(23), pages 1-23, December.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:23:p:8024-:d:692717
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    References listed on IDEAS

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    Cited by:

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    2. Majid Aghasharifian Esfahani & Mohammadmehdi Namazi & Theoklis Nikolaidis & Soheil Jafari, 2022. "Advanced Control Algorithm for FADEC Systems in the Next Generation of Turbofan Engines to Minimize Emission Levels," Mathematics, MDPI, vol. 10(10), pages 1-15, May.

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