A Resilient Frequency Regulation for Enhancing Power System Security Against Hybrid Cyber-Attacks
Abhishek Saxena, Ravi Shankar, Chandan Kumar, S. K. Parida
Abstract
Frequency Regulation (FR) is vulnerable to cyber-attacks due to their reliance on modern communication technologies. These attacks can disrupt the coordination between sub-components of the hybrid power system by influencing the communication between sensors, control centers, and actuators. Attackers can jam, alter or even delay the signals from sensors and control centers, which can severely impact power system operation. To maintain power system stability and reliability, it is imperative to develop a resilient FR mechanism that can withstand these threats. This article proposes a deep-learning-based Attack Detection and Mitigation (ADM) system for the cyber-physical model in FR analysis and an enhanced dual loop TI-LADRC with feed-forward topology for the amelioration of FR performance in the grid. ADM system estimates compares, and replaces Area Control Error (ACE) to detect and mitigate Denial of Service (DoS), False Data Injection (FDI), and Time Delay (TD) attacks. The case study is performed on a modified IEEE 39-bus and IEEE 118-bus system, considering the stochastic behavior of Renewable Energy Sources (RESs) and actual load fluctuations to ensure the efficacy of the proposed control scheme. Furthermore, real-time analysis using OPAL-RT OP5700 is presented to validate the resiliency of the control strategy and ensure improved FR analysis.