Stochastic processes in renewable power systems: From frequency domain to time domain

  • YongHua Song
  • XiaoShuang Chen
  • Jin LinEmail author
  • Feng Liu
  • YiWei Qiu
Article Special Topic: Distributed Control, Optimization and Cyber Security Strategies in Smart Grid


With the increasing penetration of renewable energy resources (RESs), the uncertainties of volatile renewable generations significantly affect the power system operation. Such uncertainties are usually modeled as stochastic variables obeying specific distributions by neglecting the temporal correlations. Conventional approaches to hedge the negative effects caused by such uncertainties are thus hard to pursue a trade-off between computation efficiency and optimality. As an alternative, the theory of stochastic process can naturally model temporal correlation in closed forms. Attracted by this feature, our research group has been conducting thorough researches in the past decade to introduce stochastic processes within renewable power systems. This paper summarizes our works from the perspective of both the frequency domain and the time domain, provides the tools for the analysis and control of power systems under a unified framework of stochastic processes, and discusses the underlying reasons that stochastic process-based approaches can perform better than conventional approaches on both computational efficiency and optimality. These work may shed a new light on the research of analysis, control and operation of renewable power systems. Finally, this paper outlooks the theoretic developments of stochastic processes in future’s renewable power systems.


renewable energy resources renewable power systems stochastic processes frequency domain time domain 


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Copyright information

© Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • YongHua Song
    • 1
    • 2
  • XiaoShuang Chen
    • 2
  • Jin Lin
    • 2
    Email author
  • Feng Liu
    • 2
  • YiWei Qiu
    • 2
  1. 1.Department of Electrical and Computer EngineeringUniversity of MacauMacauChina
  2. 2.State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment, Department of Electrical EngineeringTsinghua UniversityBeijingChina

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