Synthetic inertia emulation based on synchronous generator model using parametric identification

• Published in: 2023 International Conference on Electrical, Communication and Computer Engineering (ICECCE) pp. 1 - 6
• Main Authors: Ciceas, Paulius, Radziukynas, Virginijus
• Format: Conference Proceeding
• Language: English
• Published: IEEE 30.12.2023
• Subjects: Emulation; inertia emulation; Power system reliability; Power system stability; rate of change of frequency; Reliability; renewable energy; Stability analysis; synchronization; Synchronous generators; synthetic inertia; Transfer functions
• DOI: 10.1109/ICECCE61019.2023.10442333

As renewable energy sources (RES) generation increases, power system operators face significant challenges in maintaining the reliability and security of the power system. The rise in non-inertial power sources in small isolated power systems leads to dangerously low levels of inertia and a higher probability of detecting the rate of change of frequency (RoCoF). Regulations issued by ENTSO-E aim to provide additional mitigations and requirements for transmission system operators to ensure the stability and reliability of the power system. One approach to addressing the decreasing amount of inertia in the power system is through synthetic inertia. This paper presents a synthetic inertia methodology, allowing the derivation of a transfer function for a low-order synthetic inertia algorithm using the ARMAX parametric identification model. Based on the proposed methodology, a low-order synthetic inertia transfer function was obtained. The algorithm is easy to implement and does not require additional tuning. Furthermore, the synthetic inertia emulated by the algorithm is equivalent to the traditional inertia of synchronous generators and is measured in seconds. The paper also proposes and conducts a comparison of the performance of the resulting synthetic inertia algorithm with the inertia generated by a synchronous generator.