Decentralized Analysis Approach for Oscillation Damping in Grid-Forming and Grid-Following Heterogeneous Power Systems

TL;DR

Power systems with large shares of inverter-based resources (IBRs) experience weak damping, especially in heterogeneous grid-forming (GFM) and grid-following (GFL) settings. The authors introduce a decentralized Local Gain Condition (LGC) that constrains the local interaction gain $D_i(s)$ with the network at each IBR, ensuring no closed-loop poles enter a predefined Prohibited Domain $\Gamma$ and thereby achieving oscillation damping without global information. To reduce computation, they derive the Local Gain Boundary Condition (LGBC) and develop a parallel algorithm to compute per-IBR feasible parameter regions, enabling dynamic-agnostic, damping-constrained tuning for heterogeneous IBRs. Case studies on two- and multi-IBR systems demonstrate effective damping (e.g., damping ratio up to $\xi \approx 0.98$) and scalable computation times, validating the approach on standard IEEE test networks. This framework enables damping-constrained, IBR-agnostic design and supports grid-code development for large-scale, heterogeneous inverter-based grids.

Abstract

This letter proposes a decentralized local gain condition (LGC) to guarantee oscillation damping in inverter-based resource (IBR)-dominated power systems. The LGC constrains the dynamic gain between each IBR and the network at its point of connection. By satisfying the LGC locally, the closed-loop poles are confined to a desired region, thereby yielding system-wide oscillation damping without requiring global information. Notably, the LGC is agnostic to different IBR dynamics, well-suited for systems with heterogeneous IBRs, and flexible to various damping requirements. Moreover, a low-complexity algorithm is proposed to parameterize LGC, providing scalable and damping-constrained parameter tuning guidance for IBRs.

Figures (5)

• Figure 1: (a) Heterogeneous IBRs are interconnected to form a power system. (b) Closed-loop system model with feedback connection. (c) Oscillation damping is achieved by verifying conditions of local gain, i.e., $|D_i(s)+N_{ii}(s)|$, established by each IBR $D_i(s)$ and local network dynamics $N_{ii}(s)$.
• Figure 2: The diagram of the prohibited domain and its boundary. The vertical boundary, $\text{Re}(s)=-\sigma$, facilitates the application of the Routh-Hurwitz criterion to derive the satisfaction condition for $D_i^{ - 1}(s) + {N_{ii}(s)} \ne 0$. Specifically, when the network matrix $\textbf{N}(s)$ takes the form of a Laplacian matrix, the system inherently exhibits a pole at the origin Net.
• Figure 3: Distribution of closed-loop poles ($\text{Im}(s)\ge 0$) of the two-IBR system.
• Figure 4: Time-domain simulations on the IEEE 9-bus system DVPP: one GFM IBR at bus 2, two GFL IBRs at bus 1 and bus 3, with step power disturbances applied at bus 2 at 50 s. (a) Simulations with non-algorithm parameters. (b) Simulations with Algorithm \ref{['alg.1']}-derived parameters.
• Figure : Parameter feasible region determination.

Theorems & Definitions (2)

• proof
• proof