What is it about?
State estimation is an important tool in operation centers. The need for reliable estimates is crucial, but traditional methods are affected by the presence of bad data. This paper relies on the robust state information based on information theory and join numerical robustness features and resilience face to gross errors to the process.
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Why is it important?
Gross errors severely affect the solution of conventional state estimation. The Correntropy concepts allow to build a resilient state information that is capable to eliminate gross errors without the need of post-processing stages. However, the simple construction of the correntropy state estimator based on measurement reweighting mechanism implies on numerical ill-conditioning. To circumvent such difficulties, this paper proposed an orthogonal method for correntropy state estimation that integrates resilient features face to gross errors and numeric robustness.
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This page is a summary of: An orthogonal method for solving maximum correntropy-based power system state estimation, IET Generation Transmission & Distribution, February 2020, the Institution of Engineering and Technology (the IET), DOI: 10.1049/iet-gtd.2019.1179.
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