This paper proposes an implicit function based open-loop analysis method to detect the subsynchronous resonance(SSR), including asymmetric subsynchronous modal attraction(ASSMA) and asymmetric subsynchronous modal repulsion(ASSMR), of doubly-fed induction generator based wind farms(DFIG-WFs) penetrated power systems. As some important parameters of DFIG-WF are difficult to obtain, reinforcement learning and least squares method are applied to identify those important parameters. By predicting the location of closed-loop subsynchronous oscillation(SSO) modes based on the calculation of partial differentials of characteristic equation, both ASSMA and ASSMR can be found. The proposed method in this paper can select SSO modes which move to the right half complex planes as control parameters change. Besides, the proposed open-loop analysis method is adaptive to parameter uncertainty. Simulation studies are carried out on the 4-machine 11-bus power system to verify properties of the proposed method.

This paper proposes a residue based open-loop modal analysis method to detect low frequency modal resonance(LFMR), including asymmetric low frequency modal attraction(ALFMA) and asymmetric low frequency modal repulsion(ALFMR), of permanent magnetic synchronous generator based wind farms(PMSG-WFs) penetrated power systems. The formation of ALFMA and ALFMR caused by two open-loop low frequency oscillation(LFO) modes moving close and apart is analyzed in detail. Via predicting the trajectories of closed-loop LFO modes based on calculation of residue of open-loop LFO modes, both ALFMA and ALFMR can be detected. The proposed method can select LFO modes which move to the right half complex plane as control parameters vary. Simulation studies are carried out on a three-machine power system and a four-machine 11-bus power system to verify the properties of the proposed method.