Date of Graduation


Document Type


Degree Name

Bachelor of Science in Computer Engineering


Computer Science and Computer Engineering


Li, Qinghua

Committee Member/Reader

Patitz, Matthew

Committee Member/Second Reader

Jin, Dong


Automatic Generation Control (AGC) is a key control system utilized in electric power systems. AGC uses frequency and tie-line power flow measurements to determine the Area Control Error (ACE). ACE is then used by the AGC to adjust power generation and maintain an acceptable power system frequency. Attackers might inject false frequency and/or tie-line power flow measurements to mislead AGC into falsely adjusting power generation, which can harm power system operations. Various data forgery detection models are studied in this thesis. First, to make the use of predictive detection models easier for users, we propose a method for automated generation of detection threshold for Long-Short-Term-Memory neural network based detection models. Second, we study the performance of various detection models under low-rate false data injection attacks.


Automatic Generation Control, AGC, electric power, key control system, power generation, power system