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Title: Resilient off-grid microgrids: Capacity planning and N-1 security

Abstract

Over the past century the electric power industry has evolved to support the delivery of power over long distances with highly interconnected transmission systems. Despite this evolution, some remote communities are not connected to these systems. These communities rely on small, disconnected distribution systems, i.e., microgrids to deliver power. However, as microgrids often are not held to the same reliability standards as transmission grids, remote communities can be at risk for extended blackouts. To address this issue, we develop an optimization model and an algorithm for capacity planning and operations of microgrids that include N-1 security and other practical modeling features like AC power flow physics, component efficiencies and thermal limits. Lastly, we demonstrate the computational effectiveness of our approach on two test systems; a modified version of the IEEE 13 node test feeder and a model of a distribution system in a remote community in Alaska.

Authors:
 [1];  [2]; ORCiD logo [2];  [2]; ORCiD logo [2]; ORCiD logo [2];  [1];  [3];  [3]
  1. Clemson Univ., Clemson, SC (United States)
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Electricity Delivery and Energy Reliability (OE)
OSTI Identifier:
1372796
Report Number(s):
LA-UR-16-28050
Journal ID: ISSN 1949-3053
Grant/Contract Number:
AC52-06NA25396
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
IEEE Transactions on Smart Grid
Additional Journal Information:
Journal Volume: PP; Journal Issue: 99; Journal ID: ISSN 1949-3053
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; off-grid microgrid; mathematical programming; security-constrained power flow; decomposition algorithm

Citation Formats

Madathil, Sreenath Chalil, Yamangil, Emre, Nagarajan, Harsha, Barnes, Arthur K., Bent, Russell Whitford, Backhaus, Scott N., Mason, Scott J., Mashayekh, Salman, and Stadler, Michael. Resilient off-grid microgrids: Capacity planning and N-1 security. United States: N. p., 2017. Web. doi:10.1109/TSG.2017.2715074.
Madathil, Sreenath Chalil, Yamangil, Emre, Nagarajan, Harsha, Barnes, Arthur K., Bent, Russell Whitford, Backhaus, Scott N., Mason, Scott J., Mashayekh, Salman, & Stadler, Michael. Resilient off-grid microgrids: Capacity planning and N-1 security. United States. doi:10.1109/TSG.2017.2715074.
Madathil, Sreenath Chalil, Yamangil, Emre, Nagarajan, Harsha, Barnes, Arthur K., Bent, Russell Whitford, Backhaus, Scott N., Mason, Scott J., Mashayekh, Salman, and Stadler, Michael. Tue . "Resilient off-grid microgrids: Capacity planning and N-1 security". United States. doi:10.1109/TSG.2017.2715074.
@article{osti_1372796,
title = {Resilient off-grid microgrids: Capacity planning and N-1 security},
author = {Madathil, Sreenath Chalil and Yamangil, Emre and Nagarajan, Harsha and Barnes, Arthur K. and Bent, Russell Whitford and Backhaus, Scott N. and Mason, Scott J. and Mashayekh, Salman and Stadler, Michael},
abstractNote = {Over the past century the electric power industry has evolved to support the delivery of power over long distances with highly interconnected transmission systems. Despite this evolution, some remote communities are not connected to these systems. These communities rely on small, disconnected distribution systems, i.e., microgrids to deliver power. However, as microgrids often are not held to the same reliability standards as transmission grids, remote communities can be at risk for extended blackouts. To address this issue, we develop an optimization model and an algorithm for capacity planning and operations of microgrids that include N-1 security and other practical modeling features like AC power flow physics, component efficiencies and thermal limits. Lastly, we demonstrate the computational effectiveness of our approach on two test systems; a modified version of the IEEE 13 node test feeder and a model of a distribution system in a remote community in Alaska.},
doi = {10.1109/TSG.2017.2715074},
journal = {IEEE Transactions on Smart Grid},
number = 99,
volume = PP,
place = {United States},
year = {Tue Jun 13 00:00:00 EDT 2017},
month = {Tue Jun 13 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on June 13, 2018
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