Abstract
This paper aims to develop supplementary damping control actions of UPFCs by using forward neural networks (FNN) approximated energy function methods. The energy function based approach will first be considered for designing the supplementary damping control based on the network-preserving model. In order to provide more flexible solution, we proposed the Energy Function based Forward Neural Network Supplementary Damping (EFFNNSD) controller of UPFCs. The EFFNNSD can approximate the supplementary control action based on energy function methods. The EFFNNDS not only retain the idea of energy function methods, but also has powerful on-line learning ability for damping control adjustments. Numerical simulations on two benchmark systems have been performed to validate the proposed control for providing the extra damping and suppressing power swings even under severe operating conditions.
Original language | English |
---|---|
Title of host publication | 2018 IEEE Industry Applications Society Annual Meeting, IAS 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781538645369 |
DOIs | |
State | Published - 26 11 2018 |
Externally published | Yes |
Event | 2018 IEEE Industry Applications Society Annual Meeting, IAS 2018 - Portland, United States Duration: 23 09 2018 → 27 09 2018 |
Publication series
Name | 2018 IEEE Industry Applications Society Annual Meeting, IAS 2018 |
---|
Conference
Conference | 2018 IEEE Industry Applications Society Annual Meeting, IAS 2018 |
---|---|
Country/Territory | United States |
City | Portland |
Period | 23/09/18 → 27/09/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE
Keywords
- Damping control
- Energy functions
- Forward neural networks
- UPFC