Wind turbine generator frequency control based on improved particle swarm optimization
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TM712

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    Abstract:

    When virtual inertia control and droop control are used simultaneously in high proportion wind power system, there will be frequency regulation power competition problems. In order to improve the frequency regulation effect of the system, it coordinates and optimizes the virtual inertia control and droop control of wind turbines. A model of coordinated control strategy is constructed for wind turbines participating in frequency regulation. The particle swarm optimization algorithm is improved:according to search algebra, inertia weight ω, self learning factor c1 and social learning factor c2 are dynamically adjusted;and mutation operation is added. Based on the improved particle swarm optimization algorithm, the control parameters are optimized. The coordinated control strategy of wind turbine participating in frequency regulation is obtained. Finally, a provincial power grid is taken as an example to verify the effectiveness of control strategy and improved algorithm.

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History
  • Received:November 15,2019
  • Revised:December 26,2019
  • Adopted:October 08,2019
  • Online: June 08,2020
  • Published: May 28,2020
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