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Title: Sequential Service Restoration for Unbalanced Distribution Systems and Microgrids

The resilience and reliability of modern power systems are threatened by increasingly severe weather events and cyber-physical security events. An effective restoration methodology is desired to optimally integrate emerging smart grid technologies and pave the way for developing self-healing smart grids. In this paper, a sequential service restoration (SSR) framework is proposed to generate restoration solutions for distribution systems and microgrids in the event of large-scale power outages. The restoration solution contains a sequence of control actions that properly coordinate switches, distributed generators, and switchable loads to form multiple isolated microgrids. The SSR can be applied for three-phase unbalanced distribution systems and microgrids and can adapt to various operation conditions. Mathematical models are introduced for three-phase unbalanced power flow, voltage regulators, transformers, and loads. Furthermore, the SSR problem is formulated as a mixed-integer linear programming model, and its effectiveness is evaluated via the modified IEEE 123 node test feeder.
Authors:
 [1] ;  [2] ;  [3] ;  [1]
  1. Texas A & M Univ., College Station, TX (United States)
  2. Argonne National Lab. (ANL), Lemont, IL (United States)
  3. Argonne National Lab. (ANL), Argonne, IL (United States)
Publication Date:
Grant/Contract Number:
AC02-06CH11357
Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Power Systems
Additional Journal Information:
Journal Volume: PP; Journal Issue: 99; Journal ID: ISSN 0885-8950
Publisher:
IEEE
Research Org:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org:
USDOE Office of Electricity Delivery and Energy Reliability
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; distributed generator; distribution system; microgrid; mixed-integer linear programming (MILP); restoration sequence; self-healing; service restoration
OSTI Identifier:
1402471

Chen, Bo, Chen, Chen, Wang, Jianhui, and Butler-Purry, Karen L. Sequential Service Restoration for Unbalanced Distribution Systems and Microgrids. United States: N. p., Web. doi:10.1109/TPWRS.2017.2720122.
Chen, Bo, Chen, Chen, Wang, Jianhui, & Butler-Purry, Karen L. Sequential Service Restoration for Unbalanced Distribution Systems and Microgrids. United States. doi:10.1109/TPWRS.2017.2720122.
Chen, Bo, Chen, Chen, Wang, Jianhui, and Butler-Purry, Karen L. 2017. "Sequential Service Restoration for Unbalanced Distribution Systems and Microgrids". United States. doi:10.1109/TPWRS.2017.2720122. https://www.osti.gov/servlets/purl/1402471.
@article{osti_1402471,
title = {Sequential Service Restoration for Unbalanced Distribution Systems and Microgrids},
author = {Chen, Bo and Chen, Chen and Wang, Jianhui and Butler-Purry, Karen L.},
abstractNote = {The resilience and reliability of modern power systems are threatened by increasingly severe weather events and cyber-physical security events. An effective restoration methodology is desired to optimally integrate emerging smart grid technologies and pave the way for developing self-healing smart grids. In this paper, a sequential service restoration (SSR) framework is proposed to generate restoration solutions for distribution systems and microgrids in the event of large-scale power outages. The restoration solution contains a sequence of control actions that properly coordinate switches, distributed generators, and switchable loads to form multiple isolated microgrids. The SSR can be applied for three-phase unbalanced distribution systems and microgrids and can adapt to various operation conditions. Mathematical models are introduced for three-phase unbalanced power flow, voltage regulators, transformers, and loads. Furthermore, the SSR problem is formulated as a mixed-integer linear programming model, and its effectiveness is evaluated via the modified IEEE 123 node test feeder.},
doi = {10.1109/TPWRS.2017.2720122},
journal = {IEEE Transactions on Power Systems},
number = 99,
volume = PP,
place = {United States},
year = {2017},
month = {7}
}