Research Objective
To create a digital twin workflow that detects cyberattacks on renewable microgrid measurements and supports resilient control action for voltage, frequency and power stability.
System Architecture
The simulation can include PV, wind, BESS, grid-forming source, feeders, loads, communication-signal channels, false-data injection events, digital twin estimator and resilient controller response.
Simulation Methodology
The digital twin compares expected and measured system behaviour to identify abnormal data, control spoofing or set-point manipulation. Corrective control is evaluated under normal, attacked and recovered operating modes.
Validation Scenarios
- Normal renewable microgrid RMS operation
- False data injection on voltage, current or frequency channel
- Set-point manipulation on inverter/BESS controller
- Detection threshold and anomaly score response
- Resilient control recovery after attack
Expected Graphs and Result Discussion
A complete result section should include the main waveforms, controller response, operating status and comparison tables needed for engineering thesis documentation. For this project, the important graph set includes:
- Measured versus digital-twin estimated signals
- Attack indicator or anomaly score
- Voltage and frequency recovery
- BESS/grid-forming control action
- Normal versus attacked response comparison
Thesis and Research Extension Ideas
Kalman filtering, autoencoder detection, LSTM forecasting, blockchain logging and resilient MPC can be added for advanced cyber-physical power-system research.