State-space Modelling and Stability Analysis of ANN controller for Grid-connected VSC System
- Resource Type
- Conference
- Authors
- Bana, Prabhat Ranjan; Amin, Mohammad
- Source
- 2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT) Renewable Energy and Hydrogen Technologies (GlobConHT), 2023 IEEE IAS Global Conference on. :1-6 Mar, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Analytical models
Sensitivity analysis
Simulation
Closed box
Artificial neural networks
Power system stability
Control systems
Artificial neural network
Eigenvalues
PI-controller
Supervised learning
State-space modelling
Voltage source converter
- Language
Recently, Artificial Neural Network (ANN)-based controllers have been extensively investigated for grid-connected VSC systems. Despite having several advantageous features, the black-box modelling of the ANN controller makes it less industry attractive. This paper reveals the working mechanism of the ANN current controller and its interaction with the VSC system through the small-signal modelling approach. The ANN controller is trained with the standard PI-controller data before deploying for testing. Afterward, state-space equations of the VSC system and ANN controller are derived to develop the small-signal model. The derived model is verified against the time-domain simulation results obtained from the non-linear MATLAB/Simulink model. The small-signal model is then utilised to study the stability of the system. The system and ANN controller behaviour are also studied by performing the participation factor and parametric sensitivity analysis to the small-signal model.