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  • Open Access

Noise color shapes power grid stochastic responses

Longxin Yang and Xiaozhu Zhang (张潇竹)*

  • MOE Key Laboratory of Advanced Micro-Structured Materials, and School of Physical Science and Engineering, Tongji University, Shanghai, People's Republic of China and National Key Laboratory of Autonomous Intelligent Unmanned Systems, MOE Frontiers Science Center for Intelligent Autonomous Systems, and Shanghai Research Institute of Intelligence Science and Technology, Tongji University, Shanghai, People's Republic of China

  • *Contact author: xiaozhu_zhang@tongji.edu.cn
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Phys. Rev. E 114, 054302 – Published 2 November, 2026

DOI: https://doi.org/10.1103/tr4w-yrs1

Abstract

Real-world networked systems, such as power grids, operate inevitably under various types of noise originating from distinctive sources, which brings uncertainty and risks for systems' safe operation. As a major noise type, colored noise may enter the power system through multiple channels. For instance, through the large-scale integration of renewable energy sources and the demand-side power fluctuations, colored noise impinges on the stochastic frequency responses of power grids in a way that is not yet fully understood to date. In this work we systematically investigate the impact of noise color on the statistical properties of dynamic power grid frequency responses. Through abundant numerical simulations of a paradigmatic Kuramoto-like grid model subject to 1/fb noise with a tunable color, we demonstrate that noise with a steeper power spectrum (b≳1) dominated by low-frequency components drives power grid responses into a regime of nonstationarity and non-Gaussianity, while the responses are Gaussian for b≲1 despite the non-Gaussianity of the noise. We further show that this transition at b≈1 occurs independent of the specific topological structure underlying the power grid systems. This suggests that the intermittent renewable power feed-in with Kolmogorov exponent 5/3 may be a source of the observed non-Gaussian distribution of power grid frequency. Our results may thereby help better understand and control the collective frequency fluctuations in modern power grids.

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Phys. Rev. E 114, 054302– Published 2 November, 2026
  • Received 28 December 2025
  • Revised 21 July 2026
  • Accepted 14 October 2026
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