Optimizing microgrid architecture on Department of Defense installations

Approved for public release; distribution is unlimited === Energy managers are faced with the challenge of upgrading their installation microgrids in a tight fiscal environment, while meeting the challenges of incorporating higher percentages of renewable energy sources and providing better energy a...

Full description

Bibliographic Details
Main Author: Ulmer, Nicholas A.
Other Authors: Craparo, Emily
Published: Monterey, California: Naval Postgraduate School 2014
Online Access:http://hdl.handle.net/10945/44023
id ndltd-nps.edu-oai-calhoun.nps.edu-10945-44023
record_format oai_dc
spelling ndltd-nps.edu-oai-calhoun.nps.edu-10945-440232015-02-11T03:55:49Z Optimizing microgrid architecture on Department of Defense installations Ulmer, Nicholas A. Craparo, Emily Singham, Dashi Defense Installations Approved for public release; distribution is unlimited Energy managers are faced with the challenge of upgrading their installation microgrids in a tight fiscal environment, while meeting the challenges of incorporating higher percentages of renewable energy sources and providing better energy assurance during commercial grid failures. Incorporating renewable sources of energy into a microgrid is challenging due to the intermittent nature of supply. Using historical solar data and simulated forecasts for wind data, we formulate and exercise a capital planning optimization model designed to choose the best subset of existing and potential energy sources to maximize microgrid islanding time. Islanding time is defined as the amount of time demands can be met without connection to the commercial power grid, and it is one measure of an installation’s power resiliency. Using sensitivity analysis, we show quantitatively how increases in the capital planning budget has a direct positive impact on islanding time. However, the model also identifies areas where large increases in budget yield proportionally smaller returns in islanding time. Additionally, energy storage can provide increases in islanding time, but there are diminishing returns as the storage capacity is increased. Finally, we quantitatively show that increasing reliance on renewable power decreases sensitivity to changes in the price of fuel. 2014-12-05T20:11:00Z 2014-12-05T20:11:00Z 2014-09 Thesis http://hdl.handle.net/10945/44023 This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, it may not be copyrighted. Monterey, California: Naval Postgraduate School
collection NDLTD
sources NDLTD
description Approved for public release; distribution is unlimited === Energy managers are faced with the challenge of upgrading their installation microgrids in a tight fiscal environment, while meeting the challenges of incorporating higher percentages of renewable energy sources and providing better energy assurance during commercial grid failures. Incorporating renewable sources of energy into a microgrid is challenging due to the intermittent nature of supply. Using historical solar data and simulated forecasts for wind data, we formulate and exercise a capital planning optimization model designed to choose the best subset of existing and potential energy sources to maximize microgrid islanding time. Islanding time is defined as the amount of time demands can be met without connection to the commercial power grid, and it is one measure of an installation’s power resiliency. Using sensitivity analysis, we show quantitatively how increases in the capital planning budget has a direct positive impact on islanding time. However, the model also identifies areas where large increases in budget yield proportionally smaller returns in islanding time. Additionally, energy storage can provide increases in islanding time, but there are diminishing returns as the storage capacity is increased. Finally, we quantitatively show that increasing reliance on renewable power decreases sensitivity to changes in the price of fuel.
author2 Craparo, Emily
author_facet Craparo, Emily
Ulmer, Nicholas A.
author Ulmer, Nicholas A.
spellingShingle Ulmer, Nicholas A.
Optimizing microgrid architecture on Department of Defense installations
author_sort Ulmer, Nicholas A.
title Optimizing microgrid architecture on Department of Defense installations
title_short Optimizing microgrid architecture on Department of Defense installations
title_full Optimizing microgrid architecture on Department of Defense installations
title_fullStr Optimizing microgrid architecture on Department of Defense installations
title_full_unstemmed Optimizing microgrid architecture on Department of Defense installations
title_sort optimizing microgrid architecture on department of defense installations
publisher Monterey, California: Naval Postgraduate School
publishDate 2014
url http://hdl.handle.net/10945/44023
work_keys_str_mv AT ulmernicholasa optimizingmicrogridarchitectureondepartmentofdefenseinstallations
_version_ 1716730474146037760