Cyber-Physical Power Systems State Estimation
- 1st Edition - May 14, 2021
- Imprint: Elsevier
- Authors: Arturo Bretas, Newton Bretas, Joao B.A. London Jr, Breno Carvalho
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 0 0 3 3 - 1
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 0 3 2 2 - 6
Cyber-Physical Power System State Estimation updates classic state estimation tools to enable real-time operations and optimize reliability in modern electric power systems.… Read more
Purchase options
Institutional subscription on ScienceDirect
Request a sales quoteCyber-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.
- Develops advanced approaches to smart grid real-time monitoring through quasi-static model state estimation and non-synchronized measurements system models
- Presents a novel, extended optimization, physics-based model which identifies and corrects for measurement error presently egregiously discounted in classic models
- Demonstrates how to embed cyber-physical security into smart grids for real-time monitoring
- Introduces new approaches to calculate power flow in distribution systems and for estimating distribution system states
- Incorporates machine-learning based approaches to complement the state estimation process, including pattern recognition-based solutions, principal component analysis and support vector machines
Power system researchers primarily situated in universities and research institutions, including Ph.D. students, professors, and research engineers
Professional engineers and utility engineers responsible for power grid real-time monitoring, software developments and maintenance
Professional engineers and utility engineers responsible for power grid real-time monitoring, software developments and maintenance
- Cover image
- Title page
- Table of Contents
- Copyright
- Chapter 1: State estimation in electric power systems
- Abstract
- 1.1: Introduction
- 1.2: Organization of the book
- Chapter 2: Real-time operation of power systems
- Abstract
- 2.1: Operating states of an EPS
- 2.2: Network analysis system
- 2.3: State estimation in electric power systems
- 2.4: Exercise
- Chapter 3: Power flow in electrical systems
- Abstract
- 3.1: Introduction
- 3.2: Basic problem formulation
- 3.3: Modeling and equations for calculation of power flow
- 3.4: Nonlinear power flow
- 3.5: Power flow in distribution systems
- 3.6: Exercises
- Chapter 4: Classical static state estimation in electric power systems
- Abstract
- 4.1: Introduction
- 4.2: The measurement model
- 4.3: WLS state estimator
- 4.4: Alternative WLS estimator formulations
- 4.5: WLS estimator considering SCADA measurements and SPMs
- 4.6: Statistically robust state estimators
- 4.7: State estimators for distribution systems
- 4.8: Exercises
- Chapter 5: Qualitative characteristics of measurement sets
- Abstract
- 5.1: Observability analysis
- 5.2: Redundancy of analog measurements
- 5.3: Qualitative characteristics for metering systems containing SPMs and SCADA measurement
- 5.4: Planning and reinforcement of metering systems
- 5.5: Update of the qualitative characteristics of measurement sets
- 5.6: Qualitative characteristics considering the three-phase modeling of the electric network
- 5.7: Exercises
- Chapter 6: Gross error processing in measurements
- Abstract
- 6.1: Introduction
- 6.2: Classification of gross errors
- 6.3: Redundancy vs GE processing
- 6.4: Properties of measurement residuals
- 6.5: Detection and identification of measurements with gross errors
- 6.6: Exercises
- Chapter 7: The innovation methodology for error analysis in power systems
- Abstract
- 7.1: Introduction
- 7.2: Geometric interpretation of measurement errors
- 7.3: Innovation concept
- 7.4: Application of innovation methodology for processing GEs
- 7.5: Application of innovation methodology for parameter and topology error processing
- 7.6: Examples
- Chapter 8: Dynamic state estimation in electric power systems
- Abstract
- 8.1: Introduction
- 8.2: The history of estimation
- 8.3: Dynamic state estimation modeling
- 8.4: Dynamic state estimation GE analysis
- 8.5: Proposed dynamic state estimation formulation for GE analysis
- 8.6: Anomaly detection
- 8.7: Presentation of performed tests and analysis of results
- Chapter 9: Data-driven state estimation in electric power systems
- Abstract
- 9.1: Data-driven models
- 9.2: Ensemble CorrDet with adaptive statistics
- Index
- Edition: 1
- Published: May 14, 2021
- Imprint: Elsevier
- No. of pages: 292
- Language: English
- Paperback ISBN: 9780323900331
- eBook ISBN: 9780323903226
AB
Arturo Bretas
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.
Affiliations and expertise
Full Professor, Department of Electrical and Computer Engineering, University of Florida, Gainesville, Florida, United States of AmericaNB
Newton Bretas
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.
Affiliations and expertise
Full Professor, Department of Electrical and Computer Engineering, University of Sao Paulo, Sao Paulo, BrazilJL
Joao B.A. London Jr
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, respectively. In 2000 he received the Ph.D. degree from the University of Sao Paulo. He is currently an Associate 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 and reliability optimization.
Affiliations and expertise
Associate Professor, Department of Electrical and Computer Engineering, University of Sao Paulo, Sao Paulo, BrazilBC
Breno Carvalho
Breno E. B. Carvalho received the B.S. degree from the Federal University of Viçosa, Viçosa-MG, Brazil, in 2011, the M.Sc. and the D.Sc. degrees from EESC-University of São Paulo, São Carlos-SP, Brazil, in 2013 and 2018, respectively, both in electrical engineering. He worked as a research intern at the ECE Power Lab, University of Florida, Gainesville-FL, USA, in 2015-2016. He has been a Faculty member with the Department of Electrical Engineering, SATC University Center, Criciúma-SC, Brazil, since 2018, where he is currently a Full Time Professor. He has graduated 10 electrical engineering bachelors and published 14 scientific papers in the area of power and energy systems. His research interests are primarily concerned with real-time modelling and analysis of transmission systems, focusing on state estimation.
Affiliations and expertise
Full Time Professor, Department of Electrical Engineering, SATC University Center, Criciuma-SC, BrazilRead Cyber-Physical Power Systems State Estimation on ScienceDirect