Estimation of Frequency-Dependent Impedances in Power Grids by Deep LSTM Autoencoder and Random Forest
| Autor: | Massimo Bongiorno, Jan R. Svensson, Azam Bagheri, Irene Yu-Hua Gu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Technology
Control and Optimization Steady state (electronics) Computer science 020209 energy Energy Engineering and Power Technology 02 engineering and technology LSTM autoencoder 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Engineering (miscellaneous) Electrical impedance System bus Renewable Energy Sustainability and the Environment 020208 electrical & electronic engineering random forest regression PRBS Grid Autoencoder Random forest Power (physics) unsupervised deep learning frequency-dependent grid impedance time-series analysis Algorithm Energy (miscellaneous) Voltage |
| Zdroj: | Energies, Vol 14, Iss 3829, p 3829 (2021) Energies Volume 14 Issue 13 |
| ISSN: | 1996-1073 |
| Popis: | This paper proposes a deep-learning-based method for frequency-dependent grid impedance estimation. Through measurement of voltages and currents at a specific system bus, the estimate of the grid impedance was obtained by first extracting the sequences of the time-dependent features for the measured data using a long short-term memory autoencoder (LSTM-AE) followed by a random forest (RF) regression method to find the nonlinear map function between extracted features and the corresponding grid impedance for a wide range of frequencies. The method was trained via simulation by using time-series measurements (i.e., voltage and current) for different system parameters and verified through several case studies. The obtained results show that: (1) extracting the time-dependent features of the voltage/current data improves the performance of the RF regression method (2) the RF regression method is robust and allows grid impedance estimation within 1.5 grid cycles (3) the proposed method can effectively estimate the grid impedance both in steady state and in case of large transients like electrical faults. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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