Hartono, Joko and Pramana, Putu Agus Aditya and Kusuma, Aristo Adi and Munir, Buyung Sofiarto Power system inertia estimation based on frequency measurement. 2019 Asia Pacific Conference on Research in Industrial and Systems Engineering, APCoRISE 2019.
Full text not available from this repository.Abstract
The magnitude of system inertia determines the rate of frequency change if there is any power deviation in the system. Thus, estimation of inertia magnitude is essential to be performed in order to obtain accurate defense scheme when the system is interrupted. In addition, the inertia magnitude can also be used to determine the magnitude of power deviation, so that defense scheme can perform load shedding more accurately. Therefore, this study will discuss about the method for estimating system inertia using Artificial Neural Network (ANN) only with frequency measurement data. The training and validation data for ANN are obtained from the simulation results of power swing equation. After that, the ANN network is used to estimate the inertia magnitude of isolated system from the real measurement data. The results show that the estimation of system inertia and power deviation only with frequency measurement data will have magnitude that close to the real measurement results. Furthermore, this method for knowing the system inertia will be used in the company to determine the proper defense scheme for different system inertia.
| Item Type: | Article |
|---|---|
| Additional Information: | Date of Conference: 18-19 April 2019 Conference Location: Depok, Indonesia |
| Uncontrolled Keywords: | system inertia , estimation , power deviation , ANN |
| Subjects: | Bidang Keilmuan > Electrical Engineering Bidang Keilmuan > Elektro Arus Kuat Jurnal Bidang Keilmuan > Power System Protection Bidang Keilmuan > Teknik Elektro Tenaga Listrik Bidang Keilmuan > Tenaga Listrik |
| Divisions: | Fakultas Ketenagalistrikan dan Energi Terbarukan > S1 Teknik Elektro |
| Depositing User: | Yudha Formanto |
| Date Deposited: | 16 Oct 2025 04:14 |
| Last Modified: | 16 Oct 2025 04:14 |
| URI: | https://repository.itpln.ac.id/id/eprint/2413 |
