Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/22865
Title: Improving Dynamic Performance of Low-Inertia Systems through Eigensensitivity Optimization
Authors: Venkatraman, Ashwin 
Markovic, Uros 
Shchetinin, Dmitry 
Vrettos, Evangelos 
Aristidou, Petros 
Hug, Gabriela 
Major Field of Science: Engineering and Technology
Field Category: Electrical Engineering - Electronic Engineering - Information Engineering
Keywords: Eigensensitivity optimization;Frequency constraints;Low-inertia systems;Voltage source converter
Issue Date: Sep-2021
Source: IEEE Transactions on Power Systems, 2021, vol. 36, no. 5, pp. 4075 - 4088
Volume: 36
Issue: 5
Start page: 4075
End page: 4088
Journal: IEEE Transactions on Power Systems 
Abstract: An increasing penetration of renewable generation has led to reduced levels of rotational inertia and damping in the power network. 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 comprehensive framework for performance-based allocation of virtual inertia and damping to the converter-interfaced generators in a detailed low-inertia system. This is achieved through an iterative, eigensensitivity-based optimization algorithm that determines the optimal controller gains while simultaneously preserving small-signal stability and ensuring that the damping ratio and frequency response after disturbances are kept within acceptable limits. Two conceptually different problem formulations are presented and validated on a modified version of the well known Kundur's two-area system as well as a larger 59-bus South-East Australian network.
URI: https://hdl.handle.net/20.500.14279/22865
ISSN: 15580679
DOI: 10.1109/TPWRS.2021.3062974
Rights: © IEEE
Type: Article
Affiliation : ETH Zurich 
ABB Corporate Research Center Switzerland 
Lawrence Berkeley National Laboratory 
Cyprus University of Technology 
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