Analyzing vulnerability of electricity distribution networks to DER disruptions

TitleAnalyzing vulnerability of electricity distribution networks to DER disruptions
Publication TypeConference Paper
Year of Publication2015
AuthorsShelar, D.., and S.. Amin
Conference Name2015 American Control Conference (ACC)
Date PublishedJuly
Keywordsattacker, defender, Density estimation robust algorithm, direct load control, distributed energy resources, distributed power generation, downstream DER nodes, game theory, Games, inverters, linear power flow equations, load control cost, load flow control, Load modeling, Mathematical model, network operator, non-compromised DER, partial load reduction, power distribution protection, radial electricity distribution networks, Reactive power, sequential play game, Stackelberg game, standard bilevel network interdiction problem, structural insight, Voltage control, voltage regulation loss, vulnerability assessment
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.

DOI10.1109/ACC.2015.7171101