Evaluating Resilience of Electricity Distribution Networks via A Modification of Generalized Benders Decomposition Method
Name
1812.01746.pdf
Description
Submitted version
Size
1.57 MB
Format
Adobe PDF
Checksum (MD5)
a197f1b5a4d6746299ef8e48668688a0
Author(s)
Shelar, Devendra
Amin, Saurabh
Hiskens, Ian
Date Issued
February 2021
Journal
IEEE Transactions on Control of Network Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
D. Shelar, S. Amin and I. A. Hiskens, "Evaluating Resilience of Electricity Distribution Networks via a Modification of Generalized Benders Decomposition Method," in IEEE Transactions on Control of Network Systems, vol. 8, no. 3, pp. 1225-1238, Sept. 2021
Version
Original manuscript
Abstract
This paper presents a computational approach to evaluate resilience of electricity Distribution Networks (DNs) to cyber-physical failures. In our model, we consider an attacker who targets multiple DN components to maximize the loss of the DN operator. We consider two types of operator response: (i) Coordinated emergency response; (ii) Uncoordinated autonomous disconnects, which may lead to cascading failures. To evaluate resilience under response (i), we solve a Bilevel Mixed-Integer Second-Order Cone Program which is computationally challenging due to mixed-binary variables in the inner problem and non-convex constraints. Our approach is based on Generalized Benders Decomposition method, that achieves a reasonable tradeoff between computational time and solution accuracy. Our approach involves modifying the Benders cut based on structural insights on power flow over radial DNs. We evaluate DN resilience under response (ii) by sequentially computing autonomous component disconnects due to operating bound violations caused by the initial attack and the potential cascading failures. Our approach helps estimate the gain in resilience under response(i), relative to (ii).
MIT Department
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/TCNS.2021.3061671
