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Performance comparison of distributed state estimation algorithms for power systems

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Abstract

A newly proposed distributed dynamic state estimation algorithm based on the maximum a posteriori (MAP) technique is generalised and studied for power systems. The system model involves linear time-varying load dynamics and nonlinear measurements. The main contribution of this paper is to compare the performance and feasibility of this distributed algorithm with several existing distributed state estimation algorithms in the literature. Simulations are tested on the IEEE 39-bus and 118-bus systems under various operating conditions. The results show that this distributed algorithm performs better than distributed quasi-steady state estimation algorithms which do not use the load dynamic model. The results also show that the performance of this distributed method is very close to that by the centralized state estimation method. The merits of this algorithm over the centralized method lie in its low computational complexity and low communication load. Hence, the analysis supports the efficiency and benefits of the distributed algorithm in applications to large-scale power systems.

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Authors and Affiliations

  1. School of Control Science and Engineering, Shandong University, Jinan, 250061, China

    Yibing Sun & Huanshui Zhang

  2. School of Electrical Engineering and Computer Science, University of Newcastle, Callaghan, NSW, 2308, Australia

    Minyue Fu

  3. School of Automation, Guangdong University of Technology, Guangzhou, 510006, China

    Minyue Fu

Authors
  1. Yibing Sun
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  2. Minyue Fu
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  3. Huanshui Zhang
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Corresponding author

Correspondence to Yibing Sun.

Additional information

This research was supported by the National Natural Science Foundation of China under Grant Nos. 61120106011, 61573221, 61633014 and National Key Technology Support Program of China under Grant No. 2014BAF07B03.

This paper was recommended for publication by Editor HONG Yiguang.

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Sun, Y., Fu, M. & Zhang, H. Performance comparison of distributed state estimation algorithms for power systems. J Syst Sci Complex 30, 595–615 (2017). https://doi.org/10.1007/s11424-017-6062-3

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  • DOI: https://doi.org/10.1007/s11424-017-6062-3

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