Lee, Meng YunMeng YunLeeLai, Chao YuanChao YuanLaiCHIH-WEN LIU2024-03-132024-03-132023-01-019781665471640https://scholars.lib.ntu.edu.tw/handle/123456789/640837The ongoing trend of replacement of conventional generation units with Inverter-Based Resources (IBRs), as part of the global transition to renewable energy, is gradually reducing system inertia of the power system. System inertia plays a crucial role in developing strategies to ensure system stability as it reflects the frequency response to disturbance. In this study, the proposed method for inertia estimation is based on the swing equation using frequency measurements taken from a select number of representative buses. By modeling governor responses as a linear function of frequency deviation, the least square method can be utilized to solve the inertia estimation problem. Our study indicates that the accuracy of the system inertia estimation is greatly influenced by the selection of time windows. Therefore, the objective of this research is to identify a suitable time window for system inertia that can adapt to Svarying frequency dynamics. The proposed method is specifically designed to overcome variations in frequency dynamics. This paper treats fast frequency response (FFR) as a controllable power injection into the power system and provides a procedure for estimating system inertia in scenarios with a known amount of power injection while considering random load perturbations. To validate the effectiveness of the proposed method, 3600 different scenarios were utilized, encompassing three equivalent system models of the Taiwan power system. The results demonstrate that the proposed procedure successfully estimates system inertia, with mean absolute percentage errors of less than 3% in all scenarios.fast frequency response | governor response | swing equation | system inertia estimation[SDGs]SDG7conference paper10.1109/ETFG55873.2023.104079122-s2.0-85185820004https://api.elsevier.com/content/abstract/scopus_id/85185820004