Date of Graduation
Bachelor of Science in Computer Engineering
Computer Science and Computer Engineering
Committee Member/Second Reader
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
Dubasi, Y. R. (2021). Data Forgery Detection in Automatic Generation Control: Exploration of Automated Parameter Generation and Low-Rate Attacks. Computer Science and Computer Engineering Undergraduate Honors Theses Retrieved from https://scholarworks.uark.edu/csceuht/88
Artificial Intelligence and Robotics Commons, Controls and Control Theory Commons, Data Storage Systems Commons, Information Security Commons, Other Computer Sciences Commons, Power and Energy Commons, Signal Processing Commons, Systems and Communications Commons