Network desynchronization by non-Gaussian fluctuations

Abstract

Many networks must maintain synchrony despite the fact that they operate in noisy environments. Important examples are stochastic inertial oscillators, which are known to exhibit fluctuations with broad tails in many applications, including electric power networks with renewable energy sources. Such non-Gaussian fluctuations can result in rare network desynchronization. Here we build a general theory for inertial oscillator network desynchronization by non-Gaussian noise. We compute the rate of desynchronization and show that higher-moments of noise enter at specific powers of coupling: either speeding up or slowing down the rate exponentially depending on how noise statistics match the statistics of a network's slowest mode. Finally, we use our theory to introduce a technique that drastically reduces the effective description of network desynchronization. Most interestingly, when instability is associated with a single edge, the reduction is to one stochastic oscillator.

to appear in PRE

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Cited by in corpus (7)

• Open data base analysis of scaling and spatio-temporal properties of power grid frequencies
• Enhancing synchronization by optimal correlated noise
• Spatio-temporal complexity of power-grid frequency fluctuations
• Finite-time Correlations Boost Large Voltage-Angle Fluctuations in Electric Power Grids
• Database of Power Grid Frequency Measurements
• Reinforcement Learning Optimizes Power Dispatch in Decentralized Power Grid
• Large and small fluctuations in oscillator networks from heterogeneous and correlated noise