Suppression Strategy of Subsynchronous Oscillation in Wind Farm Based on Deep Q-leaning Network Optimization Operation Mode
With the continuous development of new power systems in China,the problem of sub-synchronous oscillation in power systems has become prominent,seriously affecting the safe and stable operation of the power grid,and the level of os-cillation damping has an important impact on the sub-synchron-ous oscillation of wind farms.As the system damping changes with the operation mode of the power system,a sub-synchron-ous oscillation suppression strategy for wind farms based on the deep Q network optimization operation mode was proposed.Firstly,the influence of pitch angle and series compensation ca-pacitor on sub-synchronous oscillation damping of wind farms was analyzed by time domain simulation,and on this basis,a joint optimization mathematical model of sub-synchronous os-cillation with adjusting doubly fed induction generator(DFIG)output by pitch angle and adjusting line series compensation by parallel capacitor was established.Secondly,the deep Q-learn-ing network algorithm was applied to the optimization solution of system oscillation damping to obtain the optimization strategy of wind turbine sub-synchronous oscillation suppres-sion,and the results are compared with the results of sub-syn-chronous oscillation suppression based on the genetic al-gorithm,The results show that this method effectively reduces the oscillation amplitude and improves the damping of the sys-tem,which verifies the rationality and superiority of this meth-od.
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