Transient Performance of Electric Power Networks under Colored Noise

TL;DR

This paper extends performance measures of power network transient responses from white noise to colored noise, accounting for renewable energy fluctuations with finite correlation times, and provides a spectral analysis of these measures.

Contribution

It introduces a closed-form expression for quadratic performance measures under colored noise and analyzes the interplay of network dynamics and noise correlation time.

Findings

Performance measures are extended to colored noise with finite correlation time.

Spectral representation relates performance to network Laplacian modes.

Balance between inertia, damping, and Laplacian modes depends on noise correlation time.

Abstract

New classes of performance measures have been recently introduced to quantify the transient response to external disturbances of coupled dynamical systems on complex networks. These performance measures are time-integrated quadratic forms in the system's coordinates or their time derivative. So far, investigations of these performance measures have been restricted to Dirac-$\delta$ impulse disturbances, in which case they can be alternatively interpreted as giving the long time output variances for stochastic white noise power demand/generation fluctuations. Strictly speaking, the approach is therefore restricted to power fluctuating on time scales shorter than the shortest time scales in the swing equations. To account for power productions from new renewable energy sources, we extend these earlier works to the relevant case of colored noise power fluctuations, with a finite correlation time $\tau > 0$. We calculate a closed-form expression for generic quadratic performance measures. Applied to specific cases, this leads to a spectral representation of performance measures as a sum over the non-zero modes of the network Laplacian. Our results emphasize the competition between inertia, damping and the Laplacian modes, whose balance is determined to a large extent by the noise correlation time scale $\tau$.