  The advent of smart power grid which plays a vital role in the upcoming smart
city era is accompanied with the implementation of a monitoring tool, called
state estimation. For the case of the unbalanced residential distribution grid,
the state estimating operation which is conducted at a regional scale is
considered as an application of the edge computing-based Internet of Things
(IoT). While the outcome of the state estimation is important to the subsequent
control activities, its accuracy heavily depends on the data integrity of the
information collected from the scattered measurement devices. This fact exposes
the vulnerability of the state estimation module under the effect of
data-driven attacks. Among these, false data injection attack (FDI) is
attracting much attention due to its capability to interfere with the normal
operation of the network without being detected. This paper presents an attack
design scheme based on a nonlinear physical-constraint model that is able to
produce an FDI attack with theoretically stealthy characteristic. To
demonstrate the effectiveness of the proposed design scheme, simulations with
the IEEE 13-node test feeder and the WSCC 9-bus system are conducted. The
experimental results indicate that not only the false positive rate of the bad
data detection mechanism is 100 per cent but the physical consequence of the
attack is severe. These results pose a serious challenge for operators in
maintaining the integrity of measurement data.
