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Cyber-Physical Power Systems State Estimation (Paperback) Loot Price: R3,486
Discovery Miles 34 860
Cyber-Physical Power Systems State Estimation (Paperback): Arturo Bretas, Newton Bretas, Joao B.A. London Jr, Breno Carvalho

Cyber-Physical Power Systems State Estimation (Paperback)

Arturo Bretas, Newton Bretas, Joao B.A. London Jr, Breno Carvalho

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Loot Price R3,486 Discovery Miles 34 860 | Repayment Terms: R327 pm x 12*

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Cyber-Physical Power System State Estimation updates classic state estimation tools to enable real-time operations and optimize reliability in modern electric power systems. The work introduces and contextualizes the core concepts and classic approaches to state estimation modeling. It builds on these classic approaches with a suite of data-driven models and non-synchronized measurement tools to reflect current measurement trends required by increasingly more sophisticated grids. Chapters outline core definitions, concepts and the network analysis procedures involved in the real-time operation of EPS. Specific sections introduce power flow problem in EPS, highlighting network component modeling and power flow equations for state estimation before addressing quasi static state estimation in electrical power systems using Weighted Least Squares (WLS) classical and alternatives formulations. Particularities of the state estimation process in distribution systems are also considered. Finally, the work goes on to address observability analysis, measurement redundancy and the processing of gross errors through the analysis of WLS static state estimator residuals.

General

Imprint: Elsevier - Health Sciences Division
Country of origin: United States
Release date: May 2021
First published: 2021
Authors: Arturo Bretas • Newton Bretas • Joao B.A. London Jr • Breno Carvalho
Dimensions: 229 x 152 x 23mm (L x W x T)
Format: Paperback
Pages: 292
ISBN-13: 978-0-323-90033-1
Categories: Books > Professional & Technical > Energy technology & engineering > Electrical engineering > Electric motors
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LSN: 0-323-90033-X
Barcode: 9780323900331

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