  The evolution of the traditional power system towards the modern smart grid
has posed many new cybersecurity challenges to this critical infrastructure.
One of the most dangerous cybersecurity threats is the False Data Injection
(FDI) attack, especially when it is capable of completely bypassing the widely
deployed Bad Data Detector of State Estimation and interrupting the normal
operation of the power system. Most of the simulated FDI attacks are designed
using simplified linearized DC model while most industry standard State
Estimation systems are based on the nonlinear AC model. In this paper, a
comprehensive FDI attack scheme is presented based on the nonlinear AC model. A
case study of the nine-bus Western System Coordinated Council (WSCC)'s power
system is provided, using an industry standard package to assess the outcomes
of the proposed design scheme. A public FDI dataset is generated as a test set
for the community to develop and evaluate new detection algorithms, which are
lacking in the field. The FDI's stealthy quality of the dataset is assessed and
proven through a preliminary analysis based on both physical power law and
statistical analysis.
