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Your search keyword '"Chawla, Astha"' showing total 11 results
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11 results on '"Chawla, Astha"'

1. Volt/VAR Optimization in the Presence of Attacks: A Real-Time Co-Simulation Study

Author

Aftab, Mohd Asim, Chawla, Astha, Vergara, Pedro P., Ahmed, Shehab, and Konstantinou, Charalambos

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

Traditionally, Volt/VAR optimization (VVO) is performed in distribution networks through legacy devices such as on-load tap changers (OLTCs), voltage regulators (VRs), and capacitor banks. With the amendment in IEEE 1547 standard, distributed energy resources (DERs) can now provide reactive power support to the grid. For this, renewable energy-based DERs, such as PV, are interfaced with the distribution networks through smart inverters (SIs). Due to the intermittent nature of such resources, VVO transforms into a dynamic problem that requires extensive communication between the VVO controller and devices performing the VVO scheme. This communication, however, can be potentially tampered with by an adversary rendering the VVO ineffective. In this regard, it is important to assess the impact of cyberattacks on the VVO scheme. This paper develops a real-time co-simulation setup to assess the effect of cyberattacks on VVO. The setup consists of a real-time power system simulator, a communication network emulator, and a master controller in a system-in-the-loop (SITL) setup. The DNP3 communication protocol is adopted for the underlying communication infrastructure. The results show that corrupted communication messages can lead to violation of voltage limits, increased number of setpoint updates of VRs, and economic loss., Comment: 2023 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)

Published
2023

6. Deep-Learning-Based Denial-of-Service Resilient Framework for Wide Area Situational Awareness of Power Systems

Author

Chawla, Astha, Panigrahi, Bijaya Ketan, and Bhalja, Bhavesh R.

Abstract

Vulnerability of the wide area measurement system (WAMS) to denial-of-service (DoS) attacks can hinder the real-time situational awareness of the grid. In this regard, a DoS cyber-attack resilient WAMS framework is presented in this article, which utilizes deep-learning-based overcomplete denoising autoencoder architecture. The proposed framework is able to reconstruct phasor measurement unit (PMU) data during DoS attacks on PMU-phasor data concentrator (PDC) connections for the entire period of power system contingencies, which helps the operator to be aware of the occurrence of any such disturbance and assist them in decision-making related to the stability of the grid. The performance of the proposed framework has been validated on western system coordinating council (WSCC) 9-bus system, which is simulated on the developed cyber-physical WAMS testbed involving real time digital simulator, hardware PMUs, hardware PDC, network switches, etc. Subsequently, the response of the suggested framework has also been evaluated on the real field PDC data gathered from the Northern Region of the Indian Power Grid. The experimental results indicate that the reconstructed PMU measurements during DoS attacks help in maintaining the dynamic visualization of system-wide information thereby ensuring the resiliency of wide area monitoring applications against DoS attacks.

Published
2023
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