Consensus + Innovations Approach for Online Distributed Multi-Area Inertia Estimation

TL;DR

The paper addresses the challenge of real-time inertia monitoring in large, multi-area power systems where centralized data collection is impractical. It introduces a fully distributed online robust C+I (consensus+innovations) estimator that uses a local swing-equation model to form a linear regression in which the unknown parameters $a^ ext{ca}_j=\omega_s/(2H^ ext{ca}_j)$ and $a^ ext{tot}=\omega_s/(2H^ ext{tot})$ are estimated from $y_j = c_j\theta$. Global exponential convergence of the estimation error is established under cooperative persistent excitation, and the inertia estimates for each area ($H^ ext{ca}_j$) and the total inertia ($H^ ext{tot}$) are computed online via $\hat{H}^ ext{tot}_j$ and $\hat{a}^ ext{tot}_j$, with a robust design to minimize $L_2$-gain against disturbances. Showcased on the New England IEEE-39 bus system, the method achieves accurate tracking under measurement noise and communication faults, enabling practical, privacy-preserving real-time inertia monitoring without a central data hub.

Abstract

The reduction of overall system inertia in modern power systems due to the increasing deployment of distributed energy resources is generally recognized as a major issue for system stability. Consequently, real-time monitoring of system inertia is critical to ensure a reliable and cost-effective system operation. Large-scale power systems are typically managed by multiple transmission system operators, making it difficult to have a central entity with access to global measurement data, which is usually required for estimating the overall system inertia. We address this problem by proposing a fully distributed inertia estimation algorithm with rigorous analytical convergence guarantees. This method requires only peer-to-peer sharing of local parameter estimates between neighboring control areas, eliminating the need for a centralized collection of real-time measurements. We robustify the algorithm in the presence of typical power system disturbances and demonstrate its performance in simulations based on the well-known New England IEEE-39 bus system.

Figures (2)

• Figure 1: Schematic representation of the considered control areas and the communication topology.
• Figure 2: Distributed inertia estimation in the presence of load variations with time-varying inertia at control area 1 and a loss of the communication link between control area 2 and 3 for $t\ge5$ s.

Theorems & Definitions (2)

• Remark 1
• Remark 2