  The cybersecurity of microgrid has received widespread attentions due to the
frequently reported attack accidents against distributed energy resource (DER)
manufactures. Numerous impact mitigation schemes have been proposed to reduce
or eliminate the impacts of false data injection attacks (FDIAs). Nevertheless,
the existing methods either requires at least one neighboring trustworthy agent
or may bring in unacceptable cost burdens. This paper aims to propose a
detection-triggered recursive impact mitigation scheme that can timely and
precisely counter the secondary FDIAs (SFDIAs) against the communication links
among DERs. Once triggering attack alarms, the power line current readings will
be utilised to observe the voltage bias injections through the physical
interconnections among DERs, based on which the current bias injections can be
recursively reconstructed from the residuals generated by unknown input
observers (UIOs). The attack impacts are eliminated by subtracting the
reconstructed bias from the incoming compromised data. The proposed mitigation
method can work even in the worst case where all communication links are under
SFDIAs and only require extra current sensors. The bias reconstruction
performance under initial errors and system noises is theoretically analysed
and the reconstruction error is proved to be bounded regardless of the
electrical parameters. To avoid deploying current sensors on all power lines, a
cost-effective deployment strategy is presented to secure a spanning tree set
of communication links that can guarantee the secondary control performance.
Extensive validation studies are conducted in MATLAB/SIMULINK and
hardware-in-the-loop (HIL) testbeds to validate the proposed method's
effectiveness against single/multiple and continuous/discontinuous SFDIAs.
