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A new interior point solver with generalized correntropy for multiple gross error suppression in state estimation

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Author(s):
Pesteh, Shabnam ; Moayyed, Hamed ; Miranda, Vladimiro ; Pereira, Jorge ; Freitas, Victor ; Simoes Costa, A. ; London Jr, J. B. A.
Total Authors: 7
Document type: Journal article
Source: Electric Power Systems Research; v. 176, p. 13-pg., 2019-11-01.
Abstract

This paper provides an answer to the problem of State Estimation (SE) with multiple simultaneous gross errors, based on Generalized Error Correntropy instead of Least Squares and on an interior point method algorithm instead of the conventional Gauss-Newton algorithm. The paper describes the mathematical model behind the new SE cost function and the construction of a suitable solver and presents illustrative numerical cases. The performance of SE with the data set contaminated with up to five simultaneous gross errors is assessed with confusion matrices, identifying false and missed detections. The superiority of the new method over the classical Largest Normalized Residual Test is confirmed at a 99% confidence level in a battery of tests. Its ability to address cases where gross errors fall on critical measurements, critical sets or leverage points is also confirmed at the same level of confidence. (AU)

FAPESP's process: 17/22297-6 - Evolution of the State Estimation process to address the new paradigms of the operation of electrical networks
Grantee:Joao Bosco Augusto London Junior
Support Opportunities: Scholarships abroad - Research