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Distributed optimization with Markovian switching targets and stochastic observation noises with applications to DC microgrids

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Abstract

A distributed optimization problem with Markovian switching targets and stochastic observation noises is considered in this paper. In order to solve target following and renewable following for microgrid (MG) optimal power balancing, and to attenuate observation noises simultaneously, distributed optimization algorithms are developed. The interaction between observation noises and Markovian switching targets may introduce a fundamental tradeoff in reducing the optimization errors and choosing the step size. Furthermore, under infrequent Markovian switching assumptions, the mean-square optimization error bounds, the switching ordinary differential equation (ODE) limit, and the asymptotic distributions of the optimization errors are established rigorously and comprehensively. A simulation example on a DC MG is presented to show the main results of the paper.

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Acknowledgements

This work was supported by Research Start-up Fund of UESTC (Grant No. Y030222059002042).

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Authors and Affiliations

  1. School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Siyu Xie & Gun Li

  2. Department of Electrical and Computer Engineering, Wayne State University, Detroit, MI, 48202, USA

    Leyi Wang & Masoud H. Nazari

  3. Department of Mathematics, University of Connecticut, Storrs, CT, 06269, USA

    George Yin

Authors
  1. Siyu Xie
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  2. Leyi Wang
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  3. Masoud H. Nazari
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  4. George Yin
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  5. Gun Li
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Correspondence to Siyu Xie.

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Xie, S., Wang, L., Nazari, M.H. et al. Distributed optimization with Markovian switching targets and stochastic observation noises with applications to DC microgrids. Sci. China Inf. Sci. 65, 222205 (2022). https://doi.org/10.1007/s11432-022-3582-5

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  • DOI: https://doi.org/10.1007/s11432-022-3582-5

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