Elsevier Cyber-Physical Power Systems State Estimation

Product Description 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. Review Authoritative, classical and novel resource on methods to optimize real-time operations for grid reliability in renewable electric power systems From the Back Cover 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 opens by introducing and contextualizing the core concepts and classic approaches to state estimation modelling. 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. It introduces the 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. The work goes on to address observability analysis and measurement redundancy. It discusses the processing of gross errors through the analysis of WLS static state estimator residuals. The work provides a new methodology for gross error processing and applies a geometric method for parameter and topology error processing. The work concludes with a lengthy section on data-driven state estimation solutions, including those supplemented with machine-learning techniques. About the Author Arturo Bretas received the B.Sc. and M.Sc. degrees in Electrical Engineering from the University of Sao Paulo in 1995 and 1998, respectively, and the Ph.D. degree from Virginia Tech in 2001. He is currently a Full Professor with the Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA. His research interests include cyber-physical systems security, smart grids, state estimation, and reliability optimization. Newton Bretas received the B.Sc. from the Federal University of Minas Gerais in 1970 and M.Sc. degrees from the University of Campinas in 1975. In 1981 he received a PhD degree from the University of Missouri. He is currently a Full Professor with the Department of Electrical and Computer Engineering, University of Sao Paulo, Sao Carlos, SP, Brazil. His research interests include power systems state estimation, nonlinear controls and reliability optimization. Joao Bosco London Junior received the B.Sc. and M.Sc. degrees in Electrical Engineering from the Federal University of Mato Grosso and University of Sao Paulo, in 1993 and 1997, resp