Research Projects

Ensuring the integrity and security of data collected from measuring devices across various locations in the distribution network is essential for its reliable operation. Adversaries can launch various types of attacks including FDIs in the ICT infrastructure of ADNs, which can significantly impact the operation of the power distribution system. While traditional voltage controllers rely on requisite communication networks, modern ICT infrastructure is vulnerable to cyber-attacks. Such vulnerabilities directly affect the performance of voltage control algorithms, and failure to isolate compromised physical nodes could undermine overall system stability. Therefore, it is crucial to address the cyber-security requirements of voltage controllers to ensure their robustness and reliability. Moreover, the growing stochasticity in ADNs is making conventional voltage control mechanism progressively ineffective, as they are based on the assumption that nodal net power injections remain constant throughout the optimization horizon. Although the Govt. of India has issued various guidelines to secure the power system against potential cyber-attacks, very limited work has been reported on securing distribution networks against intrusions. To address the research gaps, this project aims to develop a cyber-resilient Model Predictive Control (MPC)-based approach for voltage regulation in ADNs considering stealthy FDIs, DoS, and replay attacks. Besides, the proposed MPC strategy will also coordinate various volt/var devices with different temporal characteristics, addressing uncertainties in PV, EVs, and the configuration of the ADN. The embedded optimizer within the MPC solves a robust mixed-integer nonlinear programming problem to ensure effective operation. MPC is one of the most effective and suitable approaches for addressing control aspects in ADNs. While robust MPC has been designed for cyber-attack detection in various fields recently, its application remains unexplored in cyber-physical ADNs. In addition, the proposed method also seeks to achieve secondary objectives, including minimizing power losses, reducing reliance on costly control actions, and enhancing the network's energy efficiency through demand response or conservation voltage reduction. In the study, the spatial and temporal distribution characteristics of EV charging demands will be captured by predicting EV charging requirements using trip chain theory. The proposed cyber-resilient robust MPC-based voltage control algorithm will maintain the bus voltages within limits by coordinating various control devices with different temporal characteristics considering the uncertainties associated with renewables, loads, and EVs. Further, to detect cyber-attacks, the existing MPC will be augmented with a delay unit and an open-loop unit to detect and neutralize cyber-attacks while maintaining voltage magnitudes within the desired limits.