Big Data from Two Area LFC System during Normal and Cyber-Attack Conditions

Two-area Load Frequency Control (LFC) in a 50 Hz power system involves maintaining stable system frequency and regulating tie-line power flow between two interconnected areas. In each area, frequency deviations (Δf₁ and Δf2) are monitored and uploaded to the cloud for real-time processing and control. Tie-line power deviation (ΔP_tie) is computed in the cloud using data from both areas and is then sent back to Area 1 and Area 2 for control purposes. Automatic generation control (AGC) adjusts generation based on Area Control Errors (ACEs), calculated using Δf₁, Δf₂, and ΔP_tie, to maintain frequency and tie-line power close to target levels. Cloud-based monitoring enables centralized control and optimization, improving overall system performance and stability. Proper tuning of control parameters is essential for maintaining system reliability, while secure data handling and communication ensure privacy and integrity. The load frequency control where area 1 uploads Δf₁ to the cloud and area 2 uploads Δf2 to the cloud and in the cloud it computes Ptie-line and loop completes by sending the ACE back to the area 1 and area 2 where the attacks are introduced. Three types of attack namely scaling, ramp, and random attacks are given to the cloud server which manipulates the data. As a consequence of these attacks, the Load Frequency Control system becomes compromised, resulting in instability and potential grid collapse. Such disruptions highlight the critical importance of robust cybersecurity measures to safeguard the integrity and reliability of power system operations. The dataset of Load Frequency Control with attacks can be used by AI technique for attack identification and mitigation.