Power system state estimation /:
State estimation is one of the most important functions in power system operation and control. This area is concerned with the overall monitoring, control, and contingency evaluation of power systems. It is mainly aimed at providing a reliable estimate of system voltages. State estimator information...
Gespeichert in:
1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Boston :
Artech House,
[2013]
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Schriftenreihe: | Artech House power engineering series.
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Schlagworte: | |
Online-Zugang: | Volltext |
Zusammenfassung: | State estimation is one of the most important functions in power system operation and control. This area is concerned with the overall monitoring, control, and contingency evaluation of power systems. It is mainly aimed at providing a reliable estimate of system voltages. State estimator information flows to control centers, where critical decisions are made concerning power system design and operations. This valuable resource provides thorough coverage of this area, helping professionals overcome challenges involving system quality, reliability, security, stability, and economy. Engineers are. |
Beschreibung: | 7.7 Some Observations. |
Beschreibung: | 1 online resource (205 pages) : illustrations |
Bibliographie: | Includes bibliographical references and index. |
ISBN: | 9781608075126 1608075125 9781523117505 1523117508 |
Internformat
MARC
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100 | 1 | |a Ahmad, Mukhtar, |d 1948- |e author. |1 https://id.oclc.org/worldcat/entity/E39PCjKbDgdpQTwbYCtqCcc4HK | |
245 | 1 | 0 | |a Power system state estimation / |c Mukhtar Ahmad. |
264 | 1 | |a Boston : |b Artech House, |c [2013] | |
264 | 4 | |c ©2013 | |
300 | |a 1 online resource (205 pages) : |b illustrations | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
490 | 1 | |a Artech House power engineering series | |
504 | |a Includes bibliographical references and index. | ||
505 | 0 | |a Preface; 1Energy Management Systems; 1.1 Real-Time Control of a Power System; 1.2 Energy Control Center; 1.3 Security Analysis and Monitoring; 1.4 State Estimation; References; 2Power Flow Equations; 2.1 Power System Representation; 2.1.1 Transmission Lines; 2.1.2 Power Transformer; 2.2 Admittance Diagram; 2.3 Power Flow Analysis; 2.3.1 Gauss-Seidel Method; 2.3.2 Newton-Raphson Method; 2.4 Decoupled Power Flow; 2.5 Visual Tools for Power Flow Studies; 2.6 DC Power Flow; 2.7 Regulating Transformers; References; 3Weighted Least Square Estimation; 3.1 Introduction. | |
505 | 8 | |a 3.2 Properties of Weighted Least Square3.3 Maximum Likelihood Weighted Least Square State Estimation; 3.3.1 Likelihood Function; 3.4 Matrix Formulation and Measurement Measurement Model; 3.4.1 Measurement Model; 3.5 WLS State Estimation Algorithm; 3.5.1 State Estimation by Orthogonal Decomposition; 3.5.2 Equality Constrained State Estimation; 3.6 Decoupled State Estimation Method; 3.6.1 Algorithm Decoupling; 3.6.2 Model Decoupling; 3.7 DC State Estimator; References; 4Network Observability and Pseudomeasurem; 4.1 Network Graphs and Matrices; 4.2 Bus Admittance and Bus Impedance Matrices. | |
505 | 8 | |a 4.2.1 Loop to Branch Incidence Matrix4.3 Loop Equations; 4.4 Observability Analysis; 4.5 Branch Variable Formulation; 4.5.1 New Branch Variables; 4.5.2 Measurement Model Using Branch Variables; 4.5.3 Observability Analysis for Branch Variable Formulation; 4.6 Network Topology Processing; 4.7 Network Configuration; 4.7.1 Topological Observability; 4.7.2 Topological Observability Algorith; 4.8 Topology Error Processing; 4.9 Detection and Identification of Topology Errors; 4.9.1 Residual Analysis; References; 5Bad Data Detection; 5.1 Bad Data Detection in WLS Method; 5.1.1 Leverage Points. | |
505 | 8 | |a 5.2 Methods of Bad Data Detection5.2.1 Chi-Squares Test; 5.3 Identification of Bad Data; 5.3.1 Method of Normalized Residual; 5.3.2 Normalized Residuals; 5.3.3 Largest Normalized Residual Test; 5.4 Hypothesis Testing Identification; 5.5 Case Study: Improved Bad Data Processing with Strategic Placement of PMUs; References; Appendix 5A: Chi-Square Test; 6Robust State Estimation; 6.1 Basic Formulation; 6.2 Breakdown Points; 6.2.1 Leverage Points; 6.3 M-Estimators; 6.4 State Estimation Methods with Bad Data Rejection Properties; 6.4.1 Methods Using Nonquadratic Objective Functions. | |
505 | 8 | |a 6.5 Least Absolute Value State Estimator6.6 Simplex Method; 6.7 Interior Point Algorithm; 6.8 LMS Estimator; References; Appendix 6A: Linear Programming; 6A.1 Simplex Algorithm; 7 State Estimation Using Line Current Measurements; 7.1 Introduction; 7.2 Modeling State Equations; 7.3 State Estimation with Current Measurements; 7.3.1 Multiple Solutions; 7.4 Methods to Obtain a Unique Solution; 7.5 Determining the Uniqueness of a Solution Based on Numerical Methods; 7.6 Bad Data Detection in the Presence of Current Measurements; 7.6.1 WLS State Estimation; 7.6.2 WLAV Estimation. | |
500 | |a 7.7 Some Observations. | ||
520 | |a State estimation is one of the most important functions in power system operation and control. This area is concerned with the overall monitoring, control, and contingency evaluation of power systems. It is mainly aimed at providing a reliable estimate of system voltages. State estimator information flows to control centers, where critical decisions are made concerning power system design and operations. This valuable resource provides thorough coverage of this area, helping professionals overcome challenges involving system quality, reliability, security, stability, and economy. Engineers are. | ||
588 | 0 | |a Print version record. | |
650 | 0 | |a Electric power systems |x State estimation. |0 http://id.loc.gov/authorities/subjects/sh85041931 | |
650 | 6 | |a Réseaux électriques (Énergie) |x Estimation d'état. | |
650 | 7 | |a TECHNOLOGY & ENGINEERING |x Mechanical. |2 bisacsh | |
650 | 7 | |a Electric power systems |x State estimation |2 fast | |
655 | 0 | |a Electronic book. | |
655 | 4 | |a Electronic book. | |
776 | 0 | 8 | |i Print version: |a Ahmad, Mukhtar, 1948- |t Power system state estimation. |d Boston, Mass. ; London : Artech House, ©2013 |z 9781608075119 |w (DLC) 2012285556 |w (OCoLC)832570718 |
830 | 0 | |a Artech House power engineering series. |0 http://id.loc.gov/authorities/names/no2013082523 | |
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Datensatz im Suchindex
DE-BY-FWS_katkey | ZDB-4-EBA-ocn827208673 |
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adam_text | |
any_adam_object | |
author | Ahmad, Mukhtar, 1948- |
author_facet | Ahmad, Mukhtar, 1948- |
author_role | aut |
author_sort | Ahmad, Mukhtar, 1948- |
author_variant | m a ma |
building | Verbundindex |
bvnumber | localFWS |
callnumber-first | T - Technology |
callnumber-label | TK1005 |
callnumber-raw | TK1005 |
callnumber-search | TK1005 |
callnumber-sort | TK 41005 |
callnumber-subject | TK - Electrical and Nuclear Engineering |
collection | ZDB-4-EBA |
contents | Preface; 1Energy Management Systems; 1.1 Real-Time Control of a Power System; 1.2 Energy Control Center; 1.3 Security Analysis and Monitoring; 1.4 State Estimation; References; 2Power Flow Equations; 2.1 Power System Representation; 2.1.1 Transmission Lines; 2.1.2 Power Transformer; 2.2 Admittance Diagram; 2.3 Power Flow Analysis; 2.3.1 Gauss-Seidel Method; 2.3.2 Newton-Raphson Method; 2.4 Decoupled Power Flow; 2.5 Visual Tools for Power Flow Studies; 2.6 DC Power Flow; 2.7 Regulating Transformers; References; 3Weighted Least Square Estimation; 3.1 Introduction. 3.2 Properties of Weighted Least Square3.3 Maximum Likelihood Weighted Least Square State Estimation; 3.3.1 Likelihood Function; 3.4 Matrix Formulation and Measurement Measurement Model; 3.4.1 Measurement Model; 3.5 WLS State Estimation Algorithm; 3.5.1 State Estimation by Orthogonal Decomposition; 3.5.2 Equality Constrained State Estimation; 3.6 Decoupled State Estimation Method; 3.6.1 Algorithm Decoupling; 3.6.2 Model Decoupling; 3.7 DC State Estimator; References; 4Network Observability and Pseudomeasurem; 4.1 Network Graphs and Matrices; 4.2 Bus Admittance and Bus Impedance Matrices. 4.2.1 Loop to Branch Incidence Matrix4.3 Loop Equations; 4.4 Observability Analysis; 4.5 Branch Variable Formulation; 4.5.1 New Branch Variables; 4.5.2 Measurement Model Using Branch Variables; 4.5.3 Observability Analysis for Branch Variable Formulation; 4.6 Network Topology Processing; 4.7 Network Configuration; 4.7.1 Topological Observability; 4.7.2 Topological Observability Algorith; 4.8 Topology Error Processing; 4.9 Detection and Identification of Topology Errors; 4.9.1 Residual Analysis; References; 5Bad Data Detection; 5.1 Bad Data Detection in WLS Method; 5.1.1 Leverage Points. 5.2 Methods of Bad Data Detection5.2.1 Chi-Squares Test; 5.3 Identification of Bad Data; 5.3.1 Method of Normalized Residual; 5.3.2 Normalized Residuals; 5.3.3 Largest Normalized Residual Test; 5.4 Hypothesis Testing Identification; 5.5 Case Study: Improved Bad Data Processing with Strategic Placement of PMUs; References; Appendix 5A: Chi-Square Test; 6Robust State Estimation; 6.1 Basic Formulation; 6.2 Breakdown Points; 6.2.1 Leverage Points; 6.3 M-Estimators; 6.4 State Estimation Methods with Bad Data Rejection Properties; 6.4.1 Methods Using Nonquadratic Objective Functions. 6.5 Least Absolute Value State Estimator6.6 Simplex Method; 6.7 Interior Point Algorithm; 6.8 LMS Estimator; References; Appendix 6A: Linear Programming; 6A.1 Simplex Algorithm; 7 State Estimation Using Line Current Measurements; 7.1 Introduction; 7.2 Modeling State Equations; 7.3 State Estimation with Current Measurements; 7.3.1 Multiple Solutions; 7.4 Methods to Obtain a Unique Solution; 7.5 Determining the Uniqueness of a Solution Based on Numerical Methods; 7.6 Bad Data Detection in the Presence of Current Measurements; 7.6.1 WLS State Estimation; 7.6.2 WLAV Estimation. |
ctrlnum | (OCoLC)827208673 |
dewey-full | 621.31 621.319/1 |
dewey-hundreds | 600 - Technology (Applied sciences) |
dewey-ones | 621 - Applied physics |
dewey-raw | 621.31 621.319/1 |
dewey-search | 621.31 621.319/1 |
dewey-sort | 3621.31 |
dewey-tens | 620 - Engineering and allied operations |
discipline | Elektrotechnik / Elektronik / Nachrichtentechnik |
format | Electronic eBook |
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ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">Artech House power engineering series</subfield></datafield><datafield tag="504" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references and index.</subfield></datafield><datafield tag="505" ind1="0" ind2=" "><subfield code="a">Preface; 1Energy Management Systems; 1.1 Real-Time Control of a Power System; 1.2 Energy Control Center; 1.3 Security Analysis and Monitoring; 1.4 State Estimation; References; 2Power Flow Equations; 2.1 Power System Representation; 2.1.1 Transmission Lines; 2.1.2 Power Transformer; 2.2 Admittance Diagram; 2.3 Power Flow Analysis; 2.3.1 Gauss-Seidel Method; 2.3.2 Newton-Raphson Method; 2.4 Decoupled Power Flow; 2.5 Visual Tools for Power Flow Studies; 2.6 DC Power Flow; 2.7 Regulating Transformers; References; 3Weighted Least Square Estimation; 3.1 Introduction.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">3.2 Properties of Weighted Least Square3.3 Maximum Likelihood Weighted Least Square State Estimation; 3.3.1 Likelihood Function; 3.4 Matrix Formulation and Measurement Measurement Model; 3.4.1 Measurement Model; 3.5 WLS State Estimation Algorithm; 3.5.1 State Estimation by Orthogonal Decomposition; 3.5.2 Equality Constrained State Estimation; 3.6 Decoupled State Estimation Method; 3.6.1 Algorithm Decoupling; 3.6.2 Model Decoupling; 3.7 DC State Estimator; References; 4Network Observability and Pseudomeasurem; 4.1 Network Graphs and Matrices; 4.2 Bus Admittance and Bus Impedance Matrices.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">4.2.1 Loop to Branch Incidence Matrix4.3 Loop Equations; 4.4 Observability Analysis; 4.5 Branch Variable Formulation; 4.5.1 New Branch Variables; 4.5.2 Measurement Model Using Branch Variables; 4.5.3 Observability Analysis for Branch Variable Formulation; 4.6 Network Topology Processing; 4.7 Network Configuration; 4.7.1 Topological Observability; 4.7.2 Topological Observability Algorith; 4.8 Topology Error Processing; 4.9 Detection and Identification of Topology Errors; 4.9.1 Residual Analysis; References; 5Bad Data Detection; 5.1 Bad Data Detection in WLS Method; 5.1.1 Leverage Points.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">5.2 Methods of Bad Data Detection5.2.1 Chi-Squares Test; 5.3 Identification of Bad Data; 5.3.1 Method of Normalized Residual; 5.3.2 Normalized Residuals; 5.3.3 Largest Normalized Residual Test; 5.4 Hypothesis Testing Identification; 5.5 Case Study: Improved Bad Data Processing with Strategic Placement of PMUs; References; Appendix 5A: Chi-Square Test; 6Robust State Estimation; 6.1 Basic Formulation; 6.2 Breakdown Points; 6.2.1 Leverage Points; 6.3 M-Estimators; 6.4 State Estimation Methods with Bad Data Rejection Properties; 6.4.1 Methods Using Nonquadratic Objective Functions.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">6.5 Least Absolute Value State Estimator6.6 Simplex Method; 6.7 Interior Point Algorithm; 6.8 LMS Estimator; References; Appendix 6A: Linear Programming; 6A.1 Simplex Algorithm; 7 State Estimation Using Line Current Measurements; 7.1 Introduction; 7.2 Modeling State Equations; 7.3 State Estimation with Current Measurements; 7.3.1 Multiple Solutions; 7.4 Methods to Obtain a Unique Solution; 7.5 Determining the Uniqueness of a Solution Based on Numerical Methods; 7.6 Bad Data Detection in the Presence of Current Measurements; 7.6.1 WLS State Estimation; 7.6.2 WLAV Estimation.</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">7.7 Some Observations.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">State estimation is one of the most important functions in power system operation and control. This area is concerned with the overall monitoring, control, and contingency evaluation of power systems. It is mainly aimed at providing a reliable estimate of system voltages. State estimator information flows to control centers, where critical decisions are made concerning power system design and operations. This valuable resource provides thorough coverage of this area, helping professionals overcome challenges involving system quality, reliability, security, stability, and economy. 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genre | Electronic book. |
genre_facet | Electronic book. |
id | ZDB-4-EBA-ocn827208673 |
illustrated | Illustrated |
indexdate | 2024-11-27T13:25:10Z |
institution | BVB |
isbn | 9781608075126 1608075125 9781523117505 1523117508 |
language | English |
lccn | 2012285556 |
oclc_num | 827208673 |
open_access_boolean | |
owner | MAIN DE-863 DE-BY-FWS |
owner_facet | MAIN DE-863 DE-BY-FWS |
physical | 1 online resource (205 pages) : illustrations |
psigel | ZDB-4-EBA |
publishDate | 2013 |
publishDateSearch | 2013 |
publishDateSort | 2013 |
publisher | Artech House, |
record_format | marc |
series | Artech House power engineering series. |
series2 | Artech House power engineering series |
spelling | Ahmad, Mukhtar, 1948- author. https://id.oclc.org/worldcat/entity/E39PCjKbDgdpQTwbYCtqCcc4HK Power system state estimation / Mukhtar Ahmad. Boston : Artech House, [2013] ©2013 1 online resource (205 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Artech House power engineering series Includes bibliographical references and index. Preface; 1Energy Management Systems; 1.1 Real-Time Control of a Power System; 1.2 Energy Control Center; 1.3 Security Analysis and Monitoring; 1.4 State Estimation; References; 2Power Flow Equations; 2.1 Power System Representation; 2.1.1 Transmission Lines; 2.1.2 Power Transformer; 2.2 Admittance Diagram; 2.3 Power Flow Analysis; 2.3.1 Gauss-Seidel Method; 2.3.2 Newton-Raphson Method; 2.4 Decoupled Power Flow; 2.5 Visual Tools for Power Flow Studies; 2.6 DC Power Flow; 2.7 Regulating Transformers; References; 3Weighted Least Square Estimation; 3.1 Introduction. 3.2 Properties of Weighted Least Square3.3 Maximum Likelihood Weighted Least Square State Estimation; 3.3.1 Likelihood Function; 3.4 Matrix Formulation and Measurement Measurement Model; 3.4.1 Measurement Model; 3.5 WLS State Estimation Algorithm; 3.5.1 State Estimation by Orthogonal Decomposition; 3.5.2 Equality Constrained State Estimation; 3.6 Decoupled State Estimation Method; 3.6.1 Algorithm Decoupling; 3.6.2 Model Decoupling; 3.7 DC State Estimator; References; 4Network Observability and Pseudomeasurem; 4.1 Network Graphs and Matrices; 4.2 Bus Admittance and Bus Impedance Matrices. 4.2.1 Loop to Branch Incidence Matrix4.3 Loop Equations; 4.4 Observability Analysis; 4.5 Branch Variable Formulation; 4.5.1 New Branch Variables; 4.5.2 Measurement Model Using Branch Variables; 4.5.3 Observability Analysis for Branch Variable Formulation; 4.6 Network Topology Processing; 4.7 Network Configuration; 4.7.1 Topological Observability; 4.7.2 Topological Observability Algorith; 4.8 Topology Error Processing; 4.9 Detection and Identification of Topology Errors; 4.9.1 Residual Analysis; References; 5Bad Data Detection; 5.1 Bad Data Detection in WLS Method; 5.1.1 Leverage Points. 5.2 Methods of Bad Data Detection5.2.1 Chi-Squares Test; 5.3 Identification of Bad Data; 5.3.1 Method of Normalized Residual; 5.3.2 Normalized Residuals; 5.3.3 Largest Normalized Residual Test; 5.4 Hypothesis Testing Identification; 5.5 Case Study: Improved Bad Data Processing with Strategic Placement of PMUs; References; Appendix 5A: Chi-Square Test; 6Robust State Estimation; 6.1 Basic Formulation; 6.2 Breakdown Points; 6.2.1 Leverage Points; 6.3 M-Estimators; 6.4 State Estimation Methods with Bad Data Rejection Properties; 6.4.1 Methods Using Nonquadratic Objective Functions. 6.5 Least Absolute Value State Estimator6.6 Simplex Method; 6.7 Interior Point Algorithm; 6.8 LMS Estimator; References; Appendix 6A: Linear Programming; 6A.1 Simplex Algorithm; 7 State Estimation Using Line Current Measurements; 7.1 Introduction; 7.2 Modeling State Equations; 7.3 State Estimation with Current Measurements; 7.3.1 Multiple Solutions; 7.4 Methods to Obtain a Unique Solution; 7.5 Determining the Uniqueness of a Solution Based on Numerical Methods; 7.6 Bad Data Detection in the Presence of Current Measurements; 7.6.1 WLS State Estimation; 7.6.2 WLAV Estimation. 7.7 Some Observations. State estimation is one of the most important functions in power system operation and control. This area is concerned with the overall monitoring, control, and contingency evaluation of power systems. It is mainly aimed at providing a reliable estimate of system voltages. State estimator information flows to control centers, where critical decisions are made concerning power system design and operations. This valuable resource provides thorough coverage of this area, helping professionals overcome challenges involving system quality, reliability, security, stability, and economy. Engineers are. Print version record. Electric power systems State estimation. http://id.loc.gov/authorities/subjects/sh85041931 Réseaux électriques (Énergie) Estimation d'état. TECHNOLOGY & ENGINEERING Mechanical. bisacsh Electric power systems State estimation fast Electronic book. Print version: Ahmad, Mukhtar, 1948- Power system state estimation. Boston, Mass. ; London : Artech House, ©2013 9781608075119 (DLC) 2012285556 (OCoLC)832570718 Artech House power engineering series. http://id.loc.gov/authorities/names/no2013082523 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=753583 Volltext |
spellingShingle | Ahmad, Mukhtar, 1948- Power system state estimation / Artech House power engineering series. Preface; 1Energy Management Systems; 1.1 Real-Time Control of a Power System; 1.2 Energy Control Center; 1.3 Security Analysis and Monitoring; 1.4 State Estimation; References; 2Power Flow Equations; 2.1 Power System Representation; 2.1.1 Transmission Lines; 2.1.2 Power Transformer; 2.2 Admittance Diagram; 2.3 Power Flow Analysis; 2.3.1 Gauss-Seidel Method; 2.3.2 Newton-Raphson Method; 2.4 Decoupled Power Flow; 2.5 Visual Tools for Power Flow Studies; 2.6 DC Power Flow; 2.7 Regulating Transformers; References; 3Weighted Least Square Estimation; 3.1 Introduction. 3.2 Properties of Weighted Least Square3.3 Maximum Likelihood Weighted Least Square State Estimation; 3.3.1 Likelihood Function; 3.4 Matrix Formulation and Measurement Measurement Model; 3.4.1 Measurement Model; 3.5 WLS State Estimation Algorithm; 3.5.1 State Estimation by Orthogonal Decomposition; 3.5.2 Equality Constrained State Estimation; 3.6 Decoupled State Estimation Method; 3.6.1 Algorithm Decoupling; 3.6.2 Model Decoupling; 3.7 DC State Estimator; References; 4Network Observability and Pseudomeasurem; 4.1 Network Graphs and Matrices; 4.2 Bus Admittance and Bus Impedance Matrices. 4.2.1 Loop to Branch Incidence Matrix4.3 Loop Equations; 4.4 Observability Analysis; 4.5 Branch Variable Formulation; 4.5.1 New Branch Variables; 4.5.2 Measurement Model Using Branch Variables; 4.5.3 Observability Analysis for Branch Variable Formulation; 4.6 Network Topology Processing; 4.7 Network Configuration; 4.7.1 Topological Observability; 4.7.2 Topological Observability Algorith; 4.8 Topology Error Processing; 4.9 Detection and Identification of Topology Errors; 4.9.1 Residual Analysis; References; 5Bad Data Detection; 5.1 Bad Data Detection in WLS Method; 5.1.1 Leverage Points. 5.2 Methods of Bad Data Detection5.2.1 Chi-Squares Test; 5.3 Identification of Bad Data; 5.3.1 Method of Normalized Residual; 5.3.2 Normalized Residuals; 5.3.3 Largest Normalized Residual Test; 5.4 Hypothesis Testing Identification; 5.5 Case Study: Improved Bad Data Processing with Strategic Placement of PMUs; References; Appendix 5A: Chi-Square Test; 6Robust State Estimation; 6.1 Basic Formulation; 6.2 Breakdown Points; 6.2.1 Leverage Points; 6.3 M-Estimators; 6.4 State Estimation Methods with Bad Data Rejection Properties; 6.4.1 Methods Using Nonquadratic Objective Functions. 6.5 Least Absolute Value State Estimator6.6 Simplex Method; 6.7 Interior Point Algorithm; 6.8 LMS Estimator; References; Appendix 6A: Linear Programming; 6A.1 Simplex Algorithm; 7 State Estimation Using Line Current Measurements; 7.1 Introduction; 7.2 Modeling State Equations; 7.3 State Estimation with Current Measurements; 7.3.1 Multiple Solutions; 7.4 Methods to Obtain a Unique Solution; 7.5 Determining the Uniqueness of a Solution Based on Numerical Methods; 7.6 Bad Data Detection in the Presence of Current Measurements; 7.6.1 WLS State Estimation; 7.6.2 WLAV Estimation. Electric power systems State estimation. http://id.loc.gov/authorities/subjects/sh85041931 Réseaux électriques (Énergie) Estimation d'état. TECHNOLOGY & ENGINEERING Mechanical. bisacsh Electric power systems State estimation fast |
subject_GND | http://id.loc.gov/authorities/subjects/sh85041931 |
title | Power system state estimation / |
title_auth | Power system state estimation / |
title_exact_search | Power system state estimation / |
title_full | Power system state estimation / Mukhtar Ahmad. |
title_fullStr | Power system state estimation / Mukhtar Ahmad. |
title_full_unstemmed | Power system state estimation / Mukhtar Ahmad. |
title_short | Power system state estimation / |
title_sort | power system state estimation |
topic | Electric power systems State estimation. http://id.loc.gov/authorities/subjects/sh85041931 Réseaux électriques (Énergie) Estimation d'état. TECHNOLOGY & ENGINEERING Mechanical. bisacsh Electric power systems State estimation fast |
topic_facet | Electric power systems State estimation. Réseaux électriques (Énergie) Estimation d'état. TECHNOLOGY & ENGINEERING Mechanical. Electric power systems State estimation Electronic book. |
url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=753583 |
work_keys_str_mv | AT ahmadmukhtar powersystemstateestimation |