An Alternative Method for Power System Dynamic State Estimation Based on Unscented Transform
作者： Shaobu Wang , Wenzhong Gao , A. P. Sakis Meliopoulos
DOI: 10.1109/TPWRS.2011.2175255
关键词:
摘要: An efficient, timely, and accurate state estimation is a prerequisite for most energy management system (EMS) applications in power control centers. The emerging wide-area measurement systems (WAMSs) offer new opportunities developing more effective methods to monitor dynamics online. Recently, alternative have caught much attention. Due the nonlinearity of transition observation equation, linearization Jacobian matrix calculation are indispensible existing estimation. This makes WAMS' high performance compromised by burdensome calculation. In order overcome drawbacks, this study tries develop an method without Firstly, unscented transformation introduced as calculate means covariances random vector undergoing nonlinear transformation. Secondly, embedding into Kalman filter process, developed dynamic Finally, some simulation results presented showing accuracy easier implementation method.
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