Effects of Data Size on Stochastic Subspace Identification Method for Power System Electromechanical Modes

摘要

Power system electromechanical mode identification is important in mitigating poorly damped oscillations. Stochastic subspace identification (SSI) is a data driven technique used for power system modeling and analysis. The data sensitivity of SSI method and its effects on power system electromechanical mode identification is studied in this paper. The different data sizes are analyzed for effectiveness in identifying electromechanical modes present in a multi-area power system under a system disturbance. IEEE68 bus New England-New York benchmark test power system has been simulated on a real-time digital simulator for this study to generate the data needed. The oscillation frequencies including the inter-area and intra-area modes in the range from 0.3-2.0 Hz are investigated. The results prove that the data size effects the identification of electromechanical modes present.