Ambient Data Driven Recursive Mode Participation Factor Based Refined Damping Control Strategy
With the increase of scale and complexity of the interconnected power systems,the interarea low-frequency oscillation with the poor damping is the key factor affecting the security and stability of the power system.When the damping level of the power system is enhanced by the generation rescheduling,accurate selection of the regulated generator and estimation of the rescheduling amount are the key to achieve efficient damping control.First,based on the ambient data,recursive mode participation factor(ReMPF)is extracted online using the recursive subspace dynamic mode decomposition method proposed in this paper.The online tracking results accurately quantify the relationship between the generator active power and mode damping,then the key rescheduled generators can be located.On the basis of the estimation of the maximum interarea transmission power under the small signal stability(SSS)constraints,the required minimum rescheduling amount capable of enhancing the weakly damped mode to SSS security boundary is estimated,and then the optimal distribution scheme of rescheduling amount of the rescheduled generator are designed.Based on the selected candidate generators and the total re-dispatching amounts,a fully data-driven damping enhancement strategy based on the precise modulation of generator active power is further developed.The feasibility and effectiveness of the proposed method are verified by the simulation analysis of IEEE 16-machine 5-area system and an actual power grid.
万方数据
维普
