The transient stability analysis based on WAMS and online admittance parameter identification

With the scale of interconnected power grid expanding, the topology of fault network and admittance parameters become unavailable, which makes it difficult for line personnel in power system to do transient stability analyses. Aiming to solve the problem, this paper proposed the multivariate linear regression algorithm (multiple linear regression, the MLR) to identify the node admittance parameters of power system based on the data of the WAMS (wide area measurement system, the WAMS). Firstly, the MLR algorithm was used to identify the pre-fault and after-fault admittance parameters; after that, the transient energy function (transient energy function, TEF) was applied to solve the energy function of the system, CCT (critical clearing time, CCT) could be obtained ultimately. Simulation results show that the presented algorithm can simultaneously consider specific failure type of the power system and uncertain network topology structure; Furthermore, the calculation precision could get relatively higher as the admittance parameters' calculating procedures get simplified when the algorithm is applied into TEF method to analyze the transient stability. When the algorithm applied in TEF method to analyze the transient stability, the calculation precision gets relatively higher and the admittance parameter calculating procedure gets simplified.