Practical Techniques of Improving State Estimator Solution
Authors: Kiamran Radjabli
Abstract:
State Estimator became an intrinsic part of Energy Management Systems (EMS). The SCADA measurements received from the field are processed by the State Estimator in order to accurately determine the actual operating state of the power systems and provide that information to other real-time network applications. All EMS vendors offer a State Estimator functionality in their baseline products. However, setting up and ensuring that State Estimator consistently produces a reliable solution often consumes a substantial engineering effort. This paper provides generic recommendations and describes a simple practical approach to efficient tuning of State Estimator, based on the working experience with major EMS software platforms and consulting projects in many electrical utilities of the USA.
Keywords: Convergence, monitoring, performance, state estimator, troubleshooting, tuning, power systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 884References:
[1] F. Schweppe, J. Wildes, and D. Rom, Power system static state estimation: Parts I, II, and III,” Power Industry Computer Conference (PICA), Denver, Colorado June, 1969.
[2] A. Monticelli, State Estimation in Electric Power Systems: A Generalized Approach,” Kluwer, Boston, 1999.
[3] F. C. Schweppe, Power system static state estimation. Part III: Implementation, IEEE Trans. Power App. Syst., vol. 89, no. 1, pp. 130–135,Jan. 1970.
[4] A. Abur and A. G. Exposito, Electric Power System State Estimation. Theory and Implementations. New York: Marcel Dekker, 2004
[5] A.Monticelli, Electric power system state estimation, Proceedings of the IEEE, vol. 88, no. 2, pp. 262–282, 2000.
[6] R. Larson, W. Tinney, L. Hadju, and D. Piercy, State estimation in power systems. part II: Implementations and applications, IEEE Trans. Power App. Syst., vol. 89, no. 3, pp. 353–362, Mar. 1970.
[7] A. Garcıa, A. Monticelli, and P. Abreu, “Fast decoupled state estimation and bad data processing, IEEE Trans. Power App. Syst., vol. 98, no. 5, pp. 1645–1652, Sept./Oct. 1979.
[8] J. J. Allemong, L. Radu, and A. M. Sasson, A fast and reliable state estimation algorithm for AEP’s new control center, IEEE Trans. PowerApp. Syst., vol. 101, no. 4, pp. 933–944, Apr. 1982.
[9] L. Holten, A. Gjelsvik, S. Aam, F. Wu, and W. H. E. Liu, “Comparison of different methods for state estimation, IEEE Trans. Power Syst.”, vol. 3, no. 4, pp. 1798–1806, Nov. 1988.
[10] State Estimator Observability and Redundancy Requirements. ERCOT. 2004