Stochastic Resource Allocation for Electricity Distribution Network Resilience
Name
2004.04041.pdf
Description
Submitted version
Size
501.81 KB
Format
Adobe PDF
Checksum (MD5)
d8d600199b05ac53e671792680132b8f
Author(s)
Chang, Derek
Shelar, Devendra
Amin, Saurabh
Date Issued
July 2020
Journal
Proceedings of the American Control Conference
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
D. Chang, D. Shelar and S. Amin, "Stochastic Resource Allocation for Electricity Distribution Network Resilience," 2020 American Control Conference (ACC), 2020, pp. 198-203 © 2020 AACC.
Version
Original manuscript
Abstract
In recent years, it has become crucial to improve the resilience of electricity distribution networks (DNs) against storm-induced failures. Microgrids enabled by Distributed Energy Resources (DERs) can significantly help speed up re-energization of loads, particularly in the complete absence of bulk power supply. We describe an integrated approach which considers a pre-storm DER allocation problem under the uncertainty of failure scenarios as well as a post-storm dispatch problem in microgrids during the multi-period repair of the failed components. This problem is computationally challenging because the number of scenarios (resp. binary variables) increases exponentially (resp. quadratically) in the network size. Our overall solution approach for solving the resulting two-stage mixed-integer linear program (MILP) involves implementing the sample average approximation (SAA) method and Benders Decomposition. Additionally, we implement a greedy approach to reduce the computational time requirements of the post-storm repair scheduling and dispatch problem. The optimality of the resulting solution is evaluated on a modified IEEE 36-node network.
MIT Department
Massachusetts Institute of Technology. Center for Computational Science and Engineering
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.23919/ACC45564.2020.9147879
