Moving-Horizon State Estimation for Power Networks and Synchronous Generators
Author:
Affiliation:
1. ETH Zurich,Power Systems Laboratory
2. ETH Zurich,Automatic Control Laboratory
Funder
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10012119/10012131/10012261.pdf?arnumber=10012261
Reference21 articles.
1. Dynamic State Estimation of Nonlinear Differential Algebraic Equation Models of Power Networks
2. Dynamic State Estimation for Multi-Machine Power System by Unscented Kalman Filter With Enhanced Numerical Stability
3. Optimal PMU Placement for Power System Dynamic State Estimation by Using Empirical Observability Gramian
4. A Robust Iterated Extended Kalman Filter for Power System Dynamic State Estimation
5. Constrained state estimation for nonlinear discrete-time systems: stability and moving horizon approximations
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1. Optimal Power Flow With State Estimation in the Loop for Distribution Networks;IEEE Systems Journal;2023-09
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