Improving Dynamic Performance of Low-Inertia Systems through Eigensensitivity Optimization

TL;DR

This paper introduces an eigensensitivity optimization framework to optimally allocate virtual inertia and damping in low-inertia power systems, enhancing their dynamic stability amid high renewable integration.

Contribution

It proposes a novel iterative eigensensitivity-based optimization method for performance-driven placement of virtual inertia and damping devices.

Findings

Optimized virtual inertia improves system stability.

Validation on a 12-bus test system demonstrates effectiveness.

Two problem formulations show consistent results.

Abstract

An increasing penetration of renewable generation has led to reduced levels of rotational inertia and damping in the system. The consequences are higher vulnerability to disturbances and deterioration of the dynamic response of the system. To overcome these challenges, novel converter control schemes that provide virtual inertia and damping have been introduced, which raises the question of optimal distribution of such devices throughout the network. This paper presents a framework for performance-based allocation of virtual inertia and damping to the converter-interfaced generators in a low-inertia system. This is achieved through an iterative, eigensensitivity-based optimization algorithm that determines the optimal controller gains. Two conceptually different problem formulations are presented and validated on a 3-area, 12-bus test system.