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Talks  —  Devendra Shelar

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2018

  • Towards Improving the Resilience of Power Systems [pdf]
    Devendra Shelar, Saurabh Amin, Ian Hiskens
    Los Alamos National Laboratory Seminar (LANL), 2018
    Abstract. This talk consists of two parts. Part 1: This work contributes to the need for developing a systematic approach to evaluate and improve the resilience of electricity distribution networks (DNs) to cyber-physical failure events. We introduce a failure model that captures the joint impact of physical failures that result in the transmission network as voltage disturbances and cyberattacks to DN components that cause supply-demand disturbances at multiple nodes. The model is used to formulate a bilevel mixed-integer problem that captures the sequential interaction between an attacker (leader) and the DN operator (follower). The attacker (resp. operator) aims to maximize (resp. minimize) the post-contingency loss resulting from the cyber-physical failure events. We solve this problem by applying the Benders Decomposition algorithm to an equivalent min-cardinality disruption problem. Our solution approach relies on a reformulation of the " coupling constraints " which model the effects of the attacker's actions on the set of feasible operator response strategies. We evaluate the operator's value of timely response as the net reduction in post-contingency loss compared to the case with no response. This reduction can be viewed as the improvement in DN resiliency against the class of cyber-physical failure events. Part 2: In this work, we consider the problem of learning of power transmission dynamics. Synchronized readings at buses from the Phasor Measurement Units (PMUs) collected over a period of a time can be used to reconstruct the dynamic state matrix. However, practically speaking, since not every bus may have a PMU, the system is only partially observable. In this work, we propose a data-driven method based on least-squares regression. We show that under certain conditions on the connectivity between the observable and unobservable buses, it is possible to reconstruct the dynamic state matrix despite partial observability of the system.
  • Applications of Bilevel Mixed-Integer Programming to Power Systems Resilience [pdf]
    Devendra Shelar, Saurabh Amin, Ian Hiskens
    Industrial Engineering and Operations Research Seminar (IEOR), 2018
    We present an approach to improve the resilience of electricity distribution networks (DNs). We begin by motivating the N-k security problem in electricity DNs, and describing the DN vulnerabilities to a class of cyberphysical security (CPS) disruptions. We model these CPS scenarios as sequential interactions between the distribution system operator (SO) and an external adversary, which leads to a Bilevel Mixed-Integer optimization problems. Based on our quantitative framework, we present structural insights into the optimal attacker / SO strategies and how we can improve the resilient operation of radial electricity DNs.

2017

  • Quantifying Resilience of Electricity Distribution Networks to Cyberphysical Disruptions [pdf]
    Devendra Shelar, Saurabh Amin, Ian Hiskens
    Nexus Energy Seminar MIT, 2017
    Abstract. We present an approach to improve the resilience of electricity distribution networks (DNs). We begin by motivating the N-k security problem in electricity DNs, and describing the DN vulnerabilities to a class of cyberphysical security (CPS) disruptions. We model these CPS scenarios as sequential interactions between the distribution system operator (SO) and an external adversary, which leads to a multi-level optimization formulation. Our formulation enables modeling of (a) strategic CPS disruptions such as targetted supply/demand disturbances at DN nodes and voltage/frequency disturbances at the distribution substation node, and (b) a wide range of SO response strategies that include dispatch of distributed energy resources, controlled load shedding, and microgrid islanding. Based on our quantitative framework, we present structural insights into the optimal attacker / SO strategies and how we can improve the resilient operation of radial electricity DNs.
  • Compromising Security of Economic Dispatch in Power System Operations [pdf]
    Devendra Shelar, Pengfei Sun, Saurabh Amin, Saman Zonouz
    Dependable Systems and Networks (DSN), 2017
    Abstract. Power grid operations rely on the trustworthy operation of critical control center functionalities, including the socalled Economic Dispatch (ED) problem. The ED problem is a large-scale optimization problem that is periodically solved by the system operator to ensure the balance of supply and load while maintaining reliability constraints. In this paper, we propose a semantics-based attack generation and implementation approach to study the security of the ED problem. Firstly, we generate optimal attack vectors to transmission line ratings to induce maximum congestion in the critical lines, resulting in the violation of capacity limits. We formulate a bilevel optimization problem in which the attacker chooses manipulations of line capacity ratings to maximinimize the percentage line capacity violations under linear power flows.We reformulate the bilevel problem as a mixed integer linear program that can be solved efficiently. Secondly, we describe how the optimal attack vectors can be implemented in commercial energy management systems (EMSs). The attack explores the dynamic memory space of the EMS, and replaces the true line capacity ratings stored in data regions with the optimal attack vectors. In contrast to the well-known false data injection attacks to control systems that require compromising distributed sensors, our approach directly implements attacks to the control center server. Our experimental results on benchmark power systems and five widely utilized EMSs show the practical feasibility of our attack generation and implementation approach.

2016

  • Vulnerability Analysis Of Optimal Power Flow Problem Under Cyber-Physical Security Attacks [pdf]
    Devendra Shelar, Saurabh Amin
    The Institute for Operations Research and the Management Sciences (INFORMS), 2016
    Abstract. A transmission network operator (TSO) solves the classical optimal power flow (OPF) problem to ensure supply-demand balance, subject to the constraints on generator outputs, line capacities, and power flows. We study the effect of malicious parameter manipulations on the OPF solutions using a sequential game formulation. The defender is the TSO who minimizes the cost of generation. The attacker is a malicious adversary who can manipulate certain parameters of the network to introduce capacity bounds violations. We show that an approximately optimal attack can be computed by solving a MILP.

2015

  • A distributed strategy for electricity distribution network control in the face of DER compromises [pdf]
    Devendra Shelar, Jairo Giraldo, Saurabh Amin
    IEEE Conference on Decision and Control (CDC), 2015
    Abstract. We focus on the question of distributed control of electricity distribution networks in the face of security attacks to Distributed Energy Resources (DERs). Our attack model includes strategic manipulation of DER set-points by an external hacker to induce a sudden compromise of a subset of DERs connected to the network. We approach the distributed control design problem in two stages. In the first stage, we model the attacker-defender interaction as a Stackelberg game. The attacker (leader) disconnects a subset of DERs by sending them wrong set-point signals. The distribution utility (follower) response includes Volt-VAR control of non-compromised DERs and load control. The objective of the attacker (resp. defender) is to maximize (resp. minimize) the weighted sum of the total cost due to loss of frequency regulation and the cost due to loss of voltage regulation. In the second stage, we propose a distributed control (defender response) strategy for each local controller such that, if sudden supply-demand mismatch is detected (for example, due to DER compromises), the local controllers automatically respond based on their respective observations of local fluctuations in voltage and frequency. This strategy aims to achieve diversification of DER functions in the sense that each uncompromised DER node either contributes to voltage regulation (by contributing reactive power) or to frequency regulation (by contributing active power). We illustrate the effectiveness of this control strategy on a benchmark network.
  • Analyzing Vulnerability of Electricity Distribution Networks to DER Disruptions [pdf]
    Devendra Shelar, Saurabh Amin
    American Control Conference (ACC), 2015
    Abstract. We formulate a sequential (Stackelberg) game for assessing the vulnerability of radial electricity distribution networks to disruptions in Distributed Energy Resources (DERs). In this model, the attacker disrupts a subset of DER nodes by remotely manipulating the set-points of their inverters. The defender (network operator) responds by controlling the non-compromised DERs and by imposing partial load reduction via direct load control. The attacker's (resp. defender's) objective is to maximize (resp. minimize) the weighted sum of cost due to the loss of voltage regulation and the cost of load control. For the sequential play game where the attacker (resp. defender) is the leader (resp. follower) and under linear power flow equations, we show that the problem reduces to standard bilevel network interdiction problem. Under our assumptions on the attack model, we obtain a structural insight that the attacker's optimal strategy is to compromise the downstream DER nodes as opposed to the upstream ones. We present a small case study to demonstrate the applicability of our model for vulnerability assessment of distribution networks.