Network Observability Analysis through Measurement Jacobian Matrix Reduction

Slutsker, I.W.; Scudder, Jon M.

doi:10.1109/tpwrs.1987.4335128

Cited by 54 publications

(15 citation statements)

References 6 publications

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“…The system is numerically observable if (27) can be iteratively solved for a state estimate from a flat start. If the system is numerically observable, it is algebraically observable, but the converse need not hold.…”

Section: Measurement Observability Analysismentioning

confidence: 99%

Observability and criticality analysis in state estimation using integer-preserving Gaussian elimination

Korres

2012

Int. Trans. Electr. Energ. Syst.

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SUMMARY This paper presents an efficient numerical method for observability and criticality analysis in power system state estimation based on integer Gaussian elimination of integer coefficient matrices. Because all computations performed are exact, no round‐off error, numerical instability, or zero identification problems occur. The observable islands are identified in a noniterative manner by performing back substitutions on the integer triangular factors of the gain matrix. The additional measurements for placement are provided by a direct method, using the integer triangular factors of the Gram matrix associated with a reduced size Jacobian matrix. The critical measurements are identified by checking for diagonal entries of the integer residual sensitivity matrix. Implementation of the proposed method needs little additional effort, because it requires minor modifications of sparse triangular factorization and forward/backward substitution algorithms common to state estimators. The IEEE 14‐bus system is used to illustrate the steps of the proposed algorithms. Test results for a 10 343‐bus system are provided to demonstrate the features of the proposed algorithms. Copyright © 2012 John Wiley & Sons, Ltd.

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Section: Measurement Observability Analysismentioning

confidence: 99%

Observability and criticality analysis in state estimation using integer-preserving Gaussian elimination

Korres

2012

Int. Trans. Electr. Energ. Syst.

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“…Step 1: Based on analysis of symbolic Jacobian matrix [8], the methodology in [5] is used here to find out all critical 1-set, 2-set, 3-set and 4-set of the measurement system and the corresponding weak bus set. The result for the sample system in Fig.1 Step 2: BRD is determined based on its definition.…”

Section: Determination Of Brdmentioning

confidence: 99%

“…{2|2:(2-3,4,2-4) ,(2-3,4,3-4),(4,2-4,3-4)} {3|2:(2-3,4,2-4),(2-3,4,3-4),(4,2-4,3-4)} {4|2:(4,9,7-4),(4,9,9-7),(9,7-4,9-7),(2-3,4,2-4),(2-3,4,3-4),(4,2-4,3-4)} {7|0: (7)(8), (4,9,,(4,9,9-7),(9,7-4,9-7)}{8|0:(7-8)} {9|1: (9,9-10), (9,(9)(10)(11)(12)(13)(14),,(9-10,9-14),(4,9,7-4),(4,9,9-7),(9,7-4,9-7)} {10|1: (9,9-10) ,(9-10,9-14)} {14|1: (9,9-14),(9-10,9-14)} It is found that no bus is getting stronger. In other words, no obvious benefit is obtained.…”

Section: -5 71mentioning

confidence: 99%

Measurement design of data exchange for distributed multi-utility operation

Huang

Lei

2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309)

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With power market deregulation, member companies cooperate to share one whole grid system and try to achieve their own economic goals. This paper focuses on how to improve the state estimation result of member companies or ISO by exchanging raw or estimated data with neighboring member companies/ISO. The concept of Bus Redundancy Descriptor (BRD) is developed based on critical measurement set. BRD and leverage points are used as criteria to evaluate the quality of measurement systems. Accordingly, based on BRD a heuristic algorithm for measurement design under distributed multi-utility operation is presented to search for possible beneficial data exchange schemes. Numerical results verify that every member companies including ISO benefit from mutual data exchange when some principles of design are carefully applied.

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“…Two new methods to criticai measurement identification are presented in this work: the first one is based on the theory developed by BRETAS (1996a), to analyse observability using graph paths; the second method is supported by the SLUTSKER & SCUDDER (1987) theory, where identification is reached throught the analysis of the jacobian matrix.…”

Section: Uma Das Mais Importantes Responsabilidades Dos Centros Dementioning

confidence: 99%

“…Tabela 5.11 => Conjunto de medidas para o teste com a rede de 121 barras 1,3,5,6,8,10,12,13,14,17,22,25,28,29,31,33,35,Medidas de 39,40,41,42,45,48,49,50,53,55,56,57,59,60,61,Injeção 62,65,66,67,68,69,70,71,73,78,79,80,82,84,86,(barra) 87,88,89,90,91,92,96,97,99,100,101,…”

Section: -Teste Com O Sistema De 6 Barras Da Ieeementioning

confidence: 99%

Observabilidade em redes de energia: métodos de identificação de medidas críticas

Junior¹,

Augusto²

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Network Observability Analysis through Measurement Jacobian Matrix Reduction

Cited by 54 publications

References 6 publications

Observability and criticality analysis in state estimation using integer-preserving Gaussian elimination

Observability and criticality analysis in state estimation using integer-preserving Gaussian elimination

Measurement design of data exchange for distributed multi-utility operation

Observabilidade em redes de energia: métodos de identificação de medidas críticas

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