State estimation in electric power systems : a generalized approach
Author(s)
Bibliographic Information
State estimation in electric power systems : a generalized approach
(The Kluwer international series in engineering and computer science)
Springer Science+Business Media, c1999
- : [pbk.]
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Note
"Originally published by Kluwer Academic Publishers in 1999. Softcover reprint of the hardcover 1st edition 1999"--T.p. verso
Includes bibliographical references and index
Description and Table of Contents
Description
State Estimation in Electric Power Systems: A Generalized Approach provides for the first time a comprehensive introduction to the topic of state estimation at an advanced textbook level. The theory as well as practice of weighted least squares (WLS) is covered with significant rigor. Included are an in depth analysis of power flow basics, proper justification of Stott's decoupled method, observability theory and matrix solution methods. In terms of practical application, topics such as bad data analysis, combinatorial bad data analysis and multiple snap shot estimation are covered. The book caters both to the specialist as well as the newcomer to the field.
State estimation will play a crucial role in the emerging scenario of a deregulated power industry. Many market decisions will be based on knowing the present state of the system accurately.
State Estimation in Electric Power Systems: A Generalized Approach crystallizes thirty years of WLS state estimation theory and practice in power systems and focuses on techniques adopted by state estimation developers worldwide. The book also reflects the experience of developing industrial-grade state estimation software that is used in the USA, South America, and many other places in world.
Table of Contents
Acknowledgments. Foreword. 1. Real-Time Modeling of Power Networks. 2. Least-Squares and Minimum Norm Problems. 3. DC State Estimator. 4. Power Flow Equations. 5. Network Reduction and Gauss Elimination. 6. Network Topology Processing. 7. Observability Analysis. 8. Basic Techniques for Bad Data Processing. 9. Multiple Bad Data Processing Techniques. 10. AC State Estimator. 11. Estimation Based on Multiple Scans of Measurements. 12. Fast Decoupled State Estimator. 13. Numerically Robust State Estimators. A: Statistical Properties of Estimated Quantities. B: Givens Rotation. Index.
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