© The Institution of Electrical Engineers
The state vector of a power system varies with time owing to the dynamic nature of system loads. Therefore, it is necessary to establish a dynamic model for the time evolution of the state vector. The dynamic state estimation approach consists of predicting the state vector based on past estimations, followed by a filtering process performed when a new set of measurements is available. This paper presents a new algorithm for forecasting and filtering the state vector, using exponential smoothing and least-squares estimation techniques. The proposed algorithm is compared with another one based on standard Kalman filtering theory. Numerical results showing the performance for both dynamic estimators under different operational conditions are presented and discussed. Detection and identification of multiple bad data are also included. The new dynamic estimator exploiting state forecasting is extremely useful to real-time monitoring of power systems.
References
-
-
1)
-
A.E. Debs ,
R.E. Larson
.
A dynamic state estimator for tracking the state of a power system.
IEEE Trans.
,
1670 -
1678
-
2)
-
R.D. Masiello ,
F.C. Schweppe
.
A tracking static state estimator.
IEEE Trans.
,
1025 -
1033
-
3)
-
Do Coutto Filho, M.B., Leite da Silva, A.M., de Queiroz, J.F.: `Dynamic state estimation in electric power systems using Kalrrian filter', Proceedings of the 4th Brazilian Congress on automatic control, 1982, Portuguese , p. 152–157.
-
4)
-
A.H. Jazwinski
.
(1970)
, Stochastic processes and filtering theory.
-
5)
-
D.M. Falcão ,
P.A. Cooke ,
A. Brameller
.
Power system tracking state estimator and bad data processing.
IEEE Trans.
,
325 -
333
-
6)
-
Do coutto filho, M.B.: `Dynamic state estimation in electric power systems', May 1983, D.Sc. Thesis, Federal University of Rio de Janeiro, Portuguese, COPPE-U FRJ.
-
7)
-
Mahalanabis, A.K., Biswas, K.K., Singh, G.: `An algorithm for decoupled dynamic state estimators of power systems', Paper A78 573-8, IEEE PES summer meeting, July 1978, Los Angeles, CA.
-
8)
-
E. Handschin ,
F.C. Schweppe ,
J. Kohlas ,
A. Fiechter
.
Bad data analysis for power system state estimation.
IEEE Trans.
,
329 -
337
-
9)
-
S. Makridakis ,
S.C. Wheelwright
.
(1978)
, Forecasting methods and applications.
-
10)
-
F.C. Schweppe ,
E. Handschin
.
Static state estimation in electric power systems.
Proc. IEEE.
,
972 -
982
-
11)
-
K. Srinivasan ,
Y. Robichaud
.
A dynamic estimator for complex bus voltage determination.
IEEE Trans.
,
1581 -
1588
-
12)
-
G.W. Stagg ,
A.H. El-Abiad
.
(1968)
, Computer method in power system analysis.
-
13)
-
A. Garcia ,
A. Monticelli ,
P. Abreu
.
Fast decoupled state estimation and bad data processing.
IEEE Trans.
,
1645 -
1652
-
14)
-
K. Nishiya ,
J. Hasegawa ,
T. Koike
.
Dynamic state estimation including anomaly detection and identification for power systems.
IEE Proc. C, Gen., Trans. & Distrib.
,
5 ,
192 -
198
http://iet.metastore.ingenta.com/content/journals/10.1049/ip-c.1983.0046
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