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Distributed Cubature Kalman Filter with Performance Comparison for Large-scale Power Systems

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  • Control Theory and Applications
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Abstract

This paper studies a distributed cubature Kalman filter algorithm for the dynamic state estimation of a large-scale power system, which is interconnected and consists of some sub-areas. Using the hybrid measurements, each subsystem runs the proposed algorithm independently and in parallel to forecast and estimate its local state, which helps in reducing the whole execution time and the communication load without a central coordinator. The edge measurements and the exchanged information with the neighboring subsystems are utilised to correct the local state estimation of each subsystem, which makes this algorithm improve some known methods in literature. Simulation results of the IEEE 118-bus system are provided to demonstrate the performance of the proposed algorithm by comparing it with the distributed methods based on the extended Kalman filter and unscented Kalman filter.

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Authors and Affiliations

  1. School of Mathematical Sciences, University of Jinan, Jinan, Shandong, 250022, China

    Yibing Sun & Yige Zhao

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  1. Yibing Sun
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  2. Yige Zhao
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Correspondence to Yibing Sun.

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Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Recommended by Associate Editor Jun Cheng under the direction of Editor Young IL Lee. This work was supported by the National Natural Science Foundation of China under Grant 61803176, 61703180, and A Project of Shandong Province Higher Educational Science and Technology Program under Grant J18KA230.

Yibing Sun received his B.S. and M.S. degrees from the School of Mathematical Sciences, University of Jinan, China, in 2009 and 2012, respectively, and a Ph.D. degree from the School of Control Science and Engineering, Shandong University in 2017. Since 2017, he has been with the School of Mathematical Sciences, University of Jinan, China, where he is currently an assistant professor. His research interests include distributed state estimation in power systems and Kalman filter.

Yige Zhao received his B.S. and M.S. degrees from the School of Mathematical Sciences, University of Jinan, China, in 2008 and 2011, respectively, and a Ph.D. degree from the School of Control Science and Engineering, Shandong University in 2016. Since 2016, he has been with the School of Mathematical Sciences, University of Jinan, China, where he is currently an assistant professor. His research interests include fractional differential equations, fractional order system, triangular system, and time delay systems.

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Sun, Y., Zhao, Y. Distributed Cubature Kalman Filter with Performance Comparison for Large-scale Power Systems. Int. J. Control Autom. Syst. 19, 1319–1327 (2021). https://doi.org/10.1007/s12555-019-1054-9

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  • DOI: https://doi.org/10.1007/s12555-019-1054-9

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