  The number of installed remote terminal units (RTU) is on the rise,
increasing the observability and control of the power system. RTUs enable
sending data to and receiving data from a control center in the power system. A
distribution grid control center runs distribution management system (DMS)
algorithms, where the DMS takes control actions during transients and outages,
such as tripping a circuit breaker and disconnecting a controllable load to
increase the resiliency of the grid. Relying on communication-based devices
makes the control center vulnerable to cyberattacks, and attackers can send
falsified data to the control center to cause disturbances or power outages.
Previous work has conducted research on developing ways to detect a cyberattack
and ways to mitigate the adverse effects of the attack. This work studies false
data injection (FDI) attacks on the DMS algorithm of a fully inverter-based
microgrid in real time. The fully inverter-based microgrid is simulated using
an RTDS, an amplifier, an electronic load, a server, a network switch, and a
router. The DMS is integrated into the server codes and exchanges data with
RTDS through TCP/IP protocols. Moreover, a recurrent neural network (RNN)
algorithm is used to detect and mitigate the cyberattack. The effectiveness of
the detection and mitigation algorithm is tested under various scenarios using
the real-time testbed.
