Abstract
This paper presents an intelligent grid impedance identification method for grid-connected inverter, where artificial neural network (ANN) is presented to identify time-varying grid impedance. The ANN is first trained offline by self-learning algorithm, which formulates an intelligent grid impedance identification method. Then, grid-connected inverter can identify variation of grid impedance according to output current. Simulation results are given to validate the proposed impedance identification method. The proposed impedance identification method can dynamically estimate time-varying grid impedance with good self-learning capability, so as to support the integration of renewable energies into grid.
| Original language | English |
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| Title of host publication | 2022 International Power Electronics Conference (IPEC-Himeji 2022-ECCE Asia) |
| Number of pages | 6 |
| Publisher | IEEE |
| Publication date | 2022 |
| Pages | 992-997 |
| ISBN (Electronic) | 9784886864253 |
| DOIs | |
| Publication status | Published - 2022 |
| Event | IPEC 2022 ECCE Asia - Himeji city culture and convention center, Himeji, Japan Duration: 15 May 2022 → 19 May 2022 https://www.ipec2022.org/index.html |
Conference
| Conference | IPEC 2022 ECCE Asia |
|---|---|
| Location | Himeji city culture and convention center |
| Country/Territory | Japan |
| City | Himeji |
| Period | 15/05/2022 → 19/05/2022 |
| Internet address |
Keywords
- Artificial Neural Network
- Grid-connected inverter
- impedance identification
- artificial neural network
- self-learning algorithm
- time-varying impedance
- Grid impedance identification
- grid-connected inverter
- intelligence