Study on Application of Fisher Information for Power System Fault Detection

Shuping Cai, Guohai Liu


The ability to accurately detect power system faults is of vital importance for the purpose of isolating malfunctioning equipment
and resuming normal operation as soon as possible after a fault occurs. People have used a variety of electric parameters
as metrics to identify faults for a long time. The method proposed by this paper departs from the traditional approach by
introducing Fisher information (FI) as a measure of the stability of electric signals and as a criterion for making fault decisions.
In this way, a non-dimensional positive parameter is used as a single criterion to deliver fault detection for power distribution
networks. Firstly, we simplified the formula of FI and then adopted a practical method for calculating values of FI. We
demonstrated the application of FI to measure the stability of electric signals. Finally, we combined FI with wavelet analysis
to propose a novel technique for phase selection of a power distribution network with a grounding short-circuit fault, namely
the wavelet-based Fisher information (WFI). Simulation studies were then carried out to show the feasibility of the proposed

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B. Ingelsson, P.-O. Lindstrom, D. Karlsson, G. Runvik, J.-O. Sjodin,

Wide-area protection against voltage collapse, IEEE Computer Applications

in Power 10 (4) (1997) 30–35.

J. Hauer, D. Trudnowski, G. Rogers, B. Mittelstadt, Keeping an eye on

power system dynamics, IEEE Computer Applications in Power 10 (4)

(1997) 50–54.

W. Yang, Application prospects of entropy theory in power systems,

Power Construction (3) (2000) 17–19.

H. Cabezas, B. D. Fath, Towards a theory of sustainable systems, Fluid

Phase Equilibria 194 (01) (2002) 3–14.

B. D. Fath, H. Cabezas, C. W. Pawlowski, Regime changes in ecological

systems: an information theory approach, Journal of Theoretical

Biology 222 (4) (2003) 517–530.

T. Eason, H. Cabezas, Evaluating the sustainability of a regional system

using fisher information in the san luis basin, colorado, Journal of

Environmental Management 94 (1) (2012) 41–49.

B. R. Frieden, P. M. Binder, Physics from Fisher Information: A Unification,

Cambridge University Press, 2004.

A. K. Evans, Book review: Probability, statistical optics and data testing.

b.r. frieden, third edition, springer, berlin, 2001., Optics and Lasers

in Engineering 38 (5) (2002) 319–320.

A. L. Mayer, C. W. Pawlowski, H. Cabezas, Fisher information and

dynamic regime changes in ecological systems, Ecological Modelling

(1) (2006) 72–82.

A. T. Karunanithi, H. Cabezas, B. R. Frieden, C. W. Pawlowski, Detection

and assessment of ecosystem regime shifts from fisher information,

Ecology and Society 13 (1) (2008) 439–461.

B. D. Fath, H. Cabezas, Exergy and fisher information as ecological

indices, Ecological Modelling 174 (1) (2004) 25–35.

H. Cabezas, C. W. Pawlowski, A. L. Mayer, N. T. Hoagland, Sustainable

systems theory: ecological and other aspects, Journal of Cleaner

Production 13 (5) (2005) 455–467.

H. Cabezas, C. W. Pawlowski, A. L. Mayer, N. T. Hoagland, Simulated

experiments with complex sustainable systems: Ecology and technology,

Resources Conservation and Recycling 44 (3) (2005) 279–291.

Y. Shastri, U. Diwekar, H. Cabezas, J. Williamson, Is sustainability

achievable? exploring the limits of sustainability with model systems.,

Environmental Science and Technology 42 (17) (2008) 6710–6716.

Y. Shastri, U. Diwekar, H. Cabezas, Optimal control theory for sustainable

environmental management, Environmental Science and Technology

(14) (2008) 5322.

V. Rico-Ramirez, P. A. Quintana-Hernandez, J. A. Ortiz-Cruz,

S. Hernandez-Castro, Fisher information: A generalized sustainability

index?, Computer Aided Chemical Engineering 25 (08) (2008) 1155–

I. A. Rezek, S. J. Roberts, Stochastic complexity measures for physiological

signal analysis., IEEE transactions on bio-medical engineering

(9) (1998) 1186–91.

P. SM, Approximate entropy as a measure of system complexity., Proceedings

of the National Academy of Sciences of the United States of

America 88 (6) (1991) 2297–2301.

Z. Jiang, H. Feng, D. Liu, T. Wang, [analyzing sleep eeg using correlation

dimension and approximate entropy], Journal of Biomedical

Engineering 22 (4) (2005) 649.

Z. Nan, X. Liu, S. Wang, M. Wan, L. Fei, Dynamic complexity analysis

to cognitive event-related potential based on tsallis entropy and

approximate entropy, Journal of Xian Jiaotong University 41 (2) (2007)

X. U. Yong, Approximate entropy and its applications in mechanical

fault diagnosis, Information and Control 31 (6) (2002) 547–551.

H. Hu, X. Ma, Application of local wave approximate entropy in mechanical

fault diagnosis, Journal of Vibration and Shock.

F. U. Ling, H. E. Zheng-You, R. K. Mai, Q. Q. Qian, Application of

approximate entropy to fault signal analysis in electric power system,

Proceedings of the Csee 28 (28) (2008) 68–73.

S. Blanco, A. Figliola, R. Q. Quiroga, O. A. Rosso, E. Serrano, Timefrequency

analysis of electroencephalogram series. iii. wavelet packets

and information cost function, Physical Review E Statistical Physics

Plasmas Fluids and Related Interdisciplinary Topics 51 (3) (1998)

Z. Y. He, Y. M. Cai, Q. Q. Qian, Study of wavelet entropy theory and

its application in electric power system fault detection, Proceedings of

the Csee.

H. Zheng-you, L. Zhi-gang, Q. Qing-quan, Study on wavelet entropy

theory andadaptability of its application in power system, Power System

Technology 32 (32) (2004) 913–20.

X. Q. Chen, H. E. Zheng-You, F. U. Ling, Electric power transient signals

classification and recognition method based on wavelet energy

spectrum, Power System Technology 30 (17) (2006) 59–63.

H. E. Zheng-You, G. M. Luo, J. W. Yang, Power transients recognition

based on wavelet energy matrixes similarity, Journal of Electric Power

Science and Technology.

S. Mallat, A theory for multiresolution signal decomposition: The

wavelet representation, IEEE Transactions on Pattern Analysis and

Machine Intelligence 11 (7) (1989) 674–693.


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