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37 results on '"Ravikumar, Gelli"'

1. Machine Learning-Based and Physics-Based Attack Resilient Wide-Area Monitoring, Protection and Control Systems

Author

Ravikumar, Gelli, Govindarasu, Manimaran, Allgöwer, Frank, Series Editor, Morari, Manfred, Series Editor, Fleming, P., Advisory Editor, Kokotovic, P., Advisory Editor, Kurzhanski, A. B., Advisory Editor, Kwakernaak, H., Advisory Editor, Rantzer, A., Advisory Editor, Tsitsiklis, J. N., Advisory Editor, Ishii, Hideaki, editor, and Zhu, Quanyan, editor

Published
2022
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7. Project Title: AUTONOMOUS TOOLS FOR ATTACK SURFACE REDUCTION

Author

Govindarasu, Manimaran, primary, Hahn, Adam, additional, Hart, Philip, additional, Ashok, Aditya, additional, Kim, Hyekyung, additional, Ravikumar, Gelli, additional, Kumar, Vivek, additional, Wang, Pengyuan, additional, Johnson, Bev, additional, Krukow, Paul, additional, Liu, Jianzhe, additional, and Peterson, Adam, additional

Published
2021
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8. Autonomous Tools for Attack Surface Reduction (Final Report)

Author

Govindarasu, Manimaran, primary, Hahn, Adam, additional, Hart, Philip, additional, Ashok, Aditya, additional, Kim, Hyekyung (Clarisse), additional, Ravikumar, Gelli, additional, Singh, Vivek, additional, Wang, Pengyuan, additional, Johnson, Bev, additional, Krukow, Paul, additional, Liu, Jianzhe, additional, and Peterson, Adam, additional

Published
2021
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11. Chapter 8: Machine Learning-Based and Physics-Based Attack Resilient Wide-Area Monitoring, Protection and Control Systems.

Author

Ravikumar, Gelli and Govindarasu, Manimaran

Abstract

The electric power grid is a complex critical infrastructure that forms the lifeline of modern society. Securing networked Cyber-Physical Systems (CPSs), such as the power grid critical infrastructure, has emerged as paramount importance to national security and economic security. Adversaries exploit the vulnerabilities in both cyber- and physical-domains and deploy stealthymultistage cyberattacks to disrupt reliable operation of the smart grid. Recent cyberattacks (in 2015 and 2016) that targeted the Ukrainian power grid and targeted cyberattack campaign during 2017-19 demonstrate the need for techniques to detect and mitigate such attacks. These incidents demonstrated growing threats and vulnerabilities within the smart grid, where critical control centers present a major attack target and whose compromise could result in major impacts on grid operation, including blackouts. This chapter presents cyberattack surface analysis for CPS wide-area control system and proposes an attack-resilient framework for supervisory control and data acquisition, energy management system andWide-Area Monitoring, Protection and Control (WAMPAC) applications of bulk power grid. We discussMachine Learning (ML) based anomaly detection and mitigation for a WAMPAC application, namely Wide-Area Damping Control (WADC) as case study. We present the architecture of the Hardware-in-the-Loop (HIL) CPS security power grid testbed and discuss the experimental results for the case study. [ABSTRACT FROM AUTHOR]

Published
2022
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12. Anomaly Detection and Mitigation for Wide-Area Damping Control using Machine Learning

Author

G. Manimaran and Ravikumar Gelli

Subjects
business.industry, Computer science, Testbed, Stability (learning theory), Machine learning, computer.software_genre, Grid, Power (physics), Electric power system, Transmission (telecommunications), Anomaly detection, Artificial intelligence, business, Replay attack, computer
Abstract

In an interconnected multi-area power system, wide-area measurement-based damping controllers are used to damp out inter-area oscillations, which jeopardize grid stability and constrain the power flows below to their transmission capacity. The effect of wide-area damping control (WADC) significantly depends on both power and cyber systems. At the cyber system layer, an adversary can inflict the WADC process by compromising either measurement signals, control signals, or both. Stealthy and coordinated cyber-attacks may bypass the conventional cybersecurity measures to disrupt the seamless operation of WADC. This paper proposes an anomaly detection (AD) algorithm using supervised Machine Learning and a model-based logic for mitigation. The proposed AD algorithm considers measurement signals (input of WADC) and control signals (output of WADC) as input to evaluate the type of activity such as normal, perturbation (small or large signal faults), attack, and perturbation-and-attack. Upon anomaly detection, the mitigation module tunes the WADC signal and sets the control status mode as either wide-area mode or local mode. The proposed anomaly detection and mitigation (ADM) module works inline with the WADC at the control center for attack detection on both measurement and control signals. It eliminates the need for ADMs at the geographically distributed actuators. We consider coordinated and primitive data-integrity attack vectors such as pulse, ramp, relay-trip, and replay attacks. The performance of the proposed ADM algorithms was evaluated under these attack vector scenarios on a testbed environment for a 2-area 4-machine power system. The ADM module shows effective performance with 96% accuracy to detect anomalies.

Published
2020

36. Representation of short-term open access transactions using common information model.

Author

Pradeep, Yemula, Patariya, Kulbhushan, Ravikumar, Gelli, and Khaparde, S. A.

Abstract

Short term open access (STOA) transactions are one of the important mechanisms for exchange of power on Indian national grid. Currently, STOA is operated by five regional load despatch centers, leading to differences in representation of STOA transaction information. This paper presents the modeling of STOA using common information model (CIM). Use-case addressed includes, generation of a CIM/XML report which presents the STOA data for a given utility. The proposed system consists of five components namely, data acquisition, data conversion to CIM, data validation, STOA modeling in CIM and data visualization. The STOA transactions of the Western and Southern regions of India for the year 2011 have been used for building the database. The system is developed using python programming language, enterprise architect, and CIMTool for validation. The output generated creates a better understanding of market situation and thus is useful for the traders, generation utilities, discoms and system operators. [ABSTRACT FROM PUBLISHER]

Published
2012
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37. CIM for power distribution reform program in India.

Author

Sabari, C. Laakshmana, Balijepalli, V. S. K. Murthy, Thomas, Jose, Ravikumar, Gelli, and Khaparde, S. A.

Abstract

Common Information Model (CIM) has been identified as the information exchange platform for Distribution Management. Distribution utilities in India perform multiple functions of varied nature to meet equivalently myriad challenges, in many ways unique to them. This paper discusses two of them, namely, load shedding & restoration and power purchase with scheduling. Significance of load shedding & restoration activity is apparent since India is a power deficient state. Power purchase with scheduling activity gains prominence since it involves all the three modes of fixing rate of energy namely pre-fixed, negotiable and price discovery in market. Modeling of these two use cases of Indian distribution system in CIM is presented in this paper. The essential extensions required can be derived from IEC 61970, IEC 61968 and IEC 62325. The new extensions are described. These models can be used as guideline for building CIM based software applications for them. [ABSTRACT FROM PUBLISHER]

Published
2012
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