Topological Approach for Identifying Critical Measurements and Sets in State Estimation

Authors

Keywords:

state estimation, electric power systems, observability analysis, criticality analysis

Abstract

Power system state estimation (SE) is an energy management system application responsible for providing a consistent real-time database, instrumental in monitoring the system. SE input data are redundant observations (measurements) of the system state (complex bus voltages) taken in a given network configuration. Measurement redundancy is an essential requirement for the SE results' reliability, determined by the quantity, location, and type of measurements received for processing. There are two ways to approach the observability/ criticality analysis, namely topological (a graph theory-based) and numerical (performed by arithmetic operations on matrices). From the conceptual viewpoint, topological methods are adequate since the problem in question is considered structural-natured, dependent on the network topology and the type/placement of measurements. Criticality analysis has been considered vital to reveal the different network observability degrees established by the measuring system. The most severe conditions are related to the occurrence of single critical measurements and critical sets of measurements. These conditions refer to imminent network unobservability and SE limitation to detect/identify the presence of spurious measurements. This paper proposes a graph theory-based method devoted to identifying essential elements to SE. Conventional measurements (branch power flows and bus power injections) coming from SCADA systems, as well as synchrophasors (phase angles and branch current measurements), are considered. Simulation results carried out on the IEEE 14-bus test system are provided.

Downloads

Download data is not yet available.

Author Biographies

Rafael Carlos Soares Lima, UFF - Universidade Federal Fluminense

Rafael Carlos Soares Lima is currently in the first year of his doctorate in Scientific Computing and Power Systems at Universidade Federal Fluminense (UFF). He attained both a bachelor's degree in Electrical Engineering in 2018 and a master's in Scientific Computing and Power Systems in 2021 from Universidade Federal Fluminense (UFF). He is interested in the development of algorithms for electrical network analysis.

Milton Brown Do Coutto Filho, Universidade Federal Fluminense

Milton Brown Do Coutto Filho (S'76–M'78–SM'90) was born in Rio de Janeiro, Brazil, on July 10, 1953. He received the B.Sc. degree from the Catholic University of Rio de Janeiro (PUC/Rio) in 1975 and the M.Sc. and D.Sc. degrees in electrical engineering from the Federal University of Rio de Janeiro (COPPE/UFRJ), in 1978 and 1983, respectively.,His employment experience includes the position of Associate Professor at the PUC/Rio (Electrical Engineering Department, 1977–1994), and Visiting Scholar at the Northeastern University (Electrical and Computer Engineering Department, 1992–1993), Boston, MA. Since 1994, he has been with the Fluminense Federal University, Rio de Janeiro, where he is currently a Professor. His main research interests are computer applications in power systems.

Julio Cesar Stachinni de Souza, Universidade Federal Fluminense

Julio Cesar Stacchini de Souza (S’92–M’96–SM’03) received the D.Sc. degree in electrical engineering from the Catholic University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.,He worked with General Electric Co. (1988–1989), and since 1992, he has been with Fluminense Federal University, Niterói, RJ, Brazil, where he is currently a Full Professor. From 2014–2015, he was a Visiting Scholar with the Imperial College London. His research interests include computational methods for electrical power systems and intelligent system applications.

Fábio Protti, Universidade Federal Fluminense

Fabio Protti received the B.Sc. degree in computer science from the University of São Paulo (USP) in 1986 and M. Sc. And D. Sc. in engineering systems and computing from the Federal University of Rio de Janeiro (UFRJ), in 1993 and 1998, respectively. He is currently a Full Professor at Fluminense Federal University, Rio de Janeiro, Brazil. His research interests are in Graph Theory, Algorithms, and Combinatorial Optimization.

References

F. C. Schweppe, J. Wildes, and D. Rom, "Power system static state estimation: parts I, II, and III," IEEE Trans. Power App. Syst., vol. PAS-89, no. 1, pp. 120-135, Jan. 1970.

M. B. Do Coutto Filho, J. C. Stacchini de Souza, and J. D. Glover, "Roots, achievements, and prospects of power system state estimation: A review on handling corrupted measurements," Int. Trans. Electr. Energy Syst., vol. 29, no. 4, e2779, Apr. 2019.

J. Zhao, A. Gomez-Exposito, M. Netto, L. Mili, A. Abur, V. Terzija, I. Kamwa, B. C. Pal, A. K. Singh, J. Qi et al., "Power system dynamic state estimation: motivations, definitions, methodologies and future work," IEEE Trans. Power Syst., vol. 34, no. 4, pp. 3188-3198, Jul. 2019.

A. Abur and A. Gómez-Expósito, Power System State Estimation: Theory and Implementation. New York, USA: Marcel Decker, 2004.

A. Monticelli, Power System State Estimation: a Generalized Approach. Boston, MA, USA: Kluwer Academic Press, 1999.

M. B. Do Coutto Filho, J. C. Stacchini de Souza, and J. E. Villavicencio Tafur, "Quantifying observability in state estimation," IEEE Trans. Power Syst., vol. 28, no. 3, pp. 2897-2906, Aug. 2013.

A. G. Phadke and J. S. Thorp, Synchronized Phasor Measurements and Their Applications. New York, NY, USA: Springer, 2008.

K. A. Clements and P. W. Davis, "Multiple bad data detectability and identifiability: a geometric approach", IEEE Trans. Power Delivery, vol. PWRD-1, no. 3, pp. 355-360, Jul. 1986.

G. R. Krumpholz, K. A. Clements, and P. W. Davis, "Power system observability: A practical algorithm using network topology," IEEE Trans. Power App. Syst., vol. PAS-99, no. 4, pp. 1534–1542, 1980.

K. A. Clements, G. R. Krumpholz, and P. W. Davis, "State estimator measurement system reliability evaluation – an efficient algorithm based on topological observability theory," IEEE Trans. Power App. Syst., vol.PAS-101, no. 4, pp. 997–1004, 1982.

G. C. Contaxis and G. N. Korres, "A reduced model for power system observability: analysis and restoration," IEEE Trans. Power Syst., vol. 3, no. 4, pp. 1411–1417, 1988.

V. H. Quintana, A. J. A. Simões Costa, A. Mandel, "Power system topological observability using a direct graph theoretic approach," IEEE Trans. PAS, vol. 101, no. 3, pp. 617–626, 1982.

R. R. Nucera and M. L. Gilles, "Observability analysis: a new topological algorithm," IEEE Trans. Power Syst., vol. 6, no. 2, pp. 466-475, May 1991.

H. Mori and S. Tsuzuki, "A fast method for topological observability analysis using a minimum spanning tree technique," IEEE Trans. Power Syst., vol. 6, no. 2, pp. 491-500, May 1991.

A. Simões Costa, T. S. Piazza, and A. Mandel, "Qualitative methods to solve qualitative problems in power system state estimation," IEEE Trans. Power Syst., vol. 5, no. 3, pp. 941-949, Aug. 1990.

R. Tarjan, "Depth-first search and linear graph algorithms," 12th Annual Symposium on Switching and Automata Theory, pp. 114-12, 1971.

J. Edmonds, "Matroid intersection," Annuals of Discrete Mathematics, vol. 4, pp. 39-49, 1979.

C. Papadimitriou, and K. Steiglitz, Combinatorial Optimization: Algorithms and Complexity. Dover Publications, pp. 289-298, 1998.

Douglas B. West, Introduction to Graph Theory, 2nd Edition., Prentice Hall, 2001.

M. B. Do Coutto Filho, J. C. Stacchini de Souza, and M. Th. Schilling, "Handling critical data and observability," Elect. Power Components & Syst., vol. 35, no. 5, pp. 553-573, Feb. 2007.

Published

2021-09-13

How to Cite

Soares Lima, R. C., Brown Do Coutto Filho, M., Stachinni de Souza, J. C., & Protti, F. (2021). Topological Approach for Identifying Critical Measurements and Sets in State Estimation. IEEE Latin America Transactions, 20(1), 100–107. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/5145