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Title: Optimizing Service Restoration in Distribution Systems With Uncertain Repair Time and Demand

Abstract

This paper proposes a novel method to co-optimize the distribution system operation and repair crew routing for outage restoration after extreme weather events. A two-stage stochastic mixed integer linear program is developed. The first stage is to dispatch the repair crews to the damaged components. The second stage is distribution system restoration using distributed generators, and reconfiguration. We consider demand uncertainty in terms of a truncated normal forecast error distribution, and model the uncertainty of the repair time using a lognormal distribution. A new decomposition approach, combined with the progressive hedging algorithm, is developed for solving large-scale outage management problems in an effective and timely manner. Furthermore, the proposed method is validated on modified IEEE 34- and 8500-bus distribution test systems.

Authors:
ORCiD logo [1];  [1]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [3]
  1. Iowa State Univ., Ames, IA (United States)
  2. Southern Methodist Univ., Dallas, TX (United States)
  3. Argonne National Lab. (ANL), Lemont, IL (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Electricity Delivery and Energy Reliability (OE)
OSTI Identifier:
1490179
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Power Systems
Additional Journal Information:
Journal Volume: 33; Journal Issue: 6; Journal ID: ISSN 0885-8950
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
outage management; power distribution system; repair crews; routing; stochastic programming

Citation Formats

Arif, Anmar, Ma, Shanshan, Wang, Zhaoyu, Wang, Jianhui, Ryan, Sarah M., and Chen, Chen. Optimizing Service Restoration in Distribution Systems With Uncertain Repair Time and Demand. United States: N. p., 2018. Web. doi:10.1109/TPWRS.2018.2855102.
Arif, Anmar, Ma, Shanshan, Wang, Zhaoyu, Wang, Jianhui, Ryan, Sarah M., & Chen, Chen. Optimizing Service Restoration in Distribution Systems With Uncertain Repair Time and Demand. United States. doi:10.1109/TPWRS.2018.2855102.
Arif, Anmar, Ma, Shanshan, Wang, Zhaoyu, Wang, Jianhui, Ryan, Sarah M., and Chen, Chen. Wed . "Optimizing Service Restoration in Distribution Systems With Uncertain Repair Time and Demand". United States. doi:10.1109/TPWRS.2018.2855102. https://www.osti.gov/servlets/purl/1490179.
@article{osti_1490179,
title = {Optimizing Service Restoration in Distribution Systems With Uncertain Repair Time and Demand},
author = {Arif, Anmar and Ma, Shanshan and Wang, Zhaoyu and Wang, Jianhui and Ryan, Sarah M. and Chen, Chen},
abstractNote = {This paper proposes a novel method to co-optimize the distribution system operation and repair crew routing for outage restoration after extreme weather events. A two-stage stochastic mixed integer linear program is developed. The first stage is to dispatch the repair crews to the damaged components. The second stage is distribution system restoration using distributed generators, and reconfiguration. We consider demand uncertainty in terms of a truncated normal forecast error distribution, and model the uncertainty of the repair time using a lognormal distribution. A new decomposition approach, combined with the progressive hedging algorithm, is developed for solving large-scale outage management problems in an effective and timely manner. Furthermore, the proposed method is validated on modified IEEE 34- and 8500-bus distribution test systems.},
doi = {10.1109/TPWRS.2018.2855102},
journal = {IEEE Transactions on Power Systems},
number = 6,
volume = 33,
place = {United States},
year = {2018},
month = {7}
}

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