Development of scalable energy distribution models to evaluate the impacts of renewable energy on food, energy, and water system infrastructures in remote Arctic microgrids of Alaska
Thesis (M.S.) University of Alaska Fairbanks, 2020 Experience and observations from remote Alaska communities have shown that energy is inarguably at the center of food, energy, and water (FEW) security. The availability of potable water, fresh produce, food storage, or processed seafood ultimately...
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ftunivalaska:oai:scholarworks.alaska.edu:11122/12305 2023-05-15T15:03:52+02:00 Development of scalable energy distribution models to evaluate the impacts of renewable energy on food, energy, and water system infrastructures in remote Arctic microgrids of Alaska Karenzi, Justus Wies, Richard Huang, Daisy Al-Badri, Maher 2020-08 http://hdl.handle.net/11122/12305 en_US eng http://hdl.handle.net/11122/12305 Department of Electrical and Computer Engineering Electric power distribution Microgrids Smart power grids Renewable energy sources Diesel electric power plants Food security Water security Energy security Electric power plants Small power production facilities Master of Science in Electrical Engineering Thesis ms 2020 ftunivalaska 2023-02-23T21:37:53Z Thesis (M.S.) University of Alaska Fairbanks, 2020 Experience and observations from remote Alaska communities have shown that energy is inarguably at the center of food, energy, and water (FEW) security. The availability of potable water, fresh produce, food storage, or processed seafood ultimately depends on a reliable and adequate energy supply. For most communities, diesel fuel is the primary source of power, which comes at high cost because of the logistics associated with importing the fuel to these relatively isolated communities. Integrating locally available renewable energy resources not only enhances energy supply, but the impacts further translate to food and water security in remote microgrids. The focus of this work is to investigate how intermittent renewable energy sources impact community level food and water infrastructure systems in a remote Arctic microgrid. Energy distribution models are mathematically developed in MATLAB® Simulink® to identify, describe, and evaluate the connections between intermittent renewable resources and the FEW loads. Energy requirements of public water systems, greenhouses, cold storage units, seafood processing loads, and modular water and food system loads are evaluated. Then energy sources including solar PV, solar thermal collectors, wind, hydro, energy storage, and diesel electric generation are modeled and validated. Finally, simulations of scenarios using distributed energy resources to serve water and food infrastructure loads are carried out including the incorporation of dispatchable loads. The results indicate that the impacts of renewable energy on FEW infrastructure systems are highly seasonal, primarily because of the variability of renewable resources. The outcome of this work helps in gaining firsthand insights into FEW system dynamics in a remote islanded microgrid setting. National Science Foundation Chemical, Bioengineering, Environmental and Transport Systems (CBET), Track 3 Innovations at the Nexus of Food, Energy and Water Systems (INFEWS) ... Thesis Arctic Alaska University of Alaska: ScholarWorks@UA Arctic Fairbanks |
institution |
Open Polar |
collection |
University of Alaska: ScholarWorks@UA |
op_collection_id |
ftunivalaska |
language |
English |
topic |
Electric power distribution Microgrids Smart power grids Renewable energy sources Diesel electric power plants Food security Water security Energy security Electric power plants Small power production facilities Master of Science in Electrical Engineering |
spellingShingle |
Electric power distribution Microgrids Smart power grids Renewable energy sources Diesel electric power plants Food security Water security Energy security Electric power plants Small power production facilities Master of Science in Electrical Engineering Karenzi, Justus Development of scalable energy distribution models to evaluate the impacts of renewable energy on food, energy, and water system infrastructures in remote Arctic microgrids of Alaska |
topic_facet |
Electric power distribution Microgrids Smart power grids Renewable energy sources Diesel electric power plants Food security Water security Energy security Electric power plants Small power production facilities Master of Science in Electrical Engineering |
description |
Thesis (M.S.) University of Alaska Fairbanks, 2020 Experience and observations from remote Alaska communities have shown that energy is inarguably at the center of food, energy, and water (FEW) security. The availability of potable water, fresh produce, food storage, or processed seafood ultimately depends on a reliable and adequate energy supply. For most communities, diesel fuel is the primary source of power, which comes at high cost because of the logistics associated with importing the fuel to these relatively isolated communities. Integrating locally available renewable energy resources not only enhances energy supply, but the impacts further translate to food and water security in remote microgrids. The focus of this work is to investigate how intermittent renewable energy sources impact community level food and water infrastructure systems in a remote Arctic microgrid. Energy distribution models are mathematically developed in MATLAB® Simulink® to identify, describe, and evaluate the connections between intermittent renewable resources and the FEW loads. Energy requirements of public water systems, greenhouses, cold storage units, seafood processing loads, and modular water and food system loads are evaluated. Then energy sources including solar PV, solar thermal collectors, wind, hydro, energy storage, and diesel electric generation are modeled and validated. Finally, simulations of scenarios using distributed energy resources to serve water and food infrastructure loads are carried out including the incorporation of dispatchable loads. The results indicate that the impacts of renewable energy on FEW infrastructure systems are highly seasonal, primarily because of the variability of renewable resources. The outcome of this work helps in gaining firsthand insights into FEW system dynamics in a remote islanded microgrid setting. National Science Foundation Chemical, Bioengineering, Environmental and Transport Systems (CBET), Track 3 Innovations at the Nexus of Food, Energy and Water Systems (INFEWS) ... |
author2 |
Wies, Richard Huang, Daisy Al-Badri, Maher |
format |
Thesis |
author |
Karenzi, Justus |
author_facet |
Karenzi, Justus |
author_sort |
Karenzi, Justus |
title |
Development of scalable energy distribution models to evaluate the impacts of renewable energy on food, energy, and water system infrastructures in remote Arctic microgrids of Alaska |
title_short |
Development of scalable energy distribution models to evaluate the impacts of renewable energy on food, energy, and water system infrastructures in remote Arctic microgrids of Alaska |
title_full |
Development of scalable energy distribution models to evaluate the impacts of renewable energy on food, energy, and water system infrastructures in remote Arctic microgrids of Alaska |
title_fullStr |
Development of scalable energy distribution models to evaluate the impacts of renewable energy on food, energy, and water system infrastructures in remote Arctic microgrids of Alaska |
title_full_unstemmed |
Development of scalable energy distribution models to evaluate the impacts of renewable energy on food, energy, and water system infrastructures in remote Arctic microgrids of Alaska |
title_sort |
development of scalable energy distribution models to evaluate the impacts of renewable energy on food, energy, and water system infrastructures in remote arctic microgrids of alaska |
publishDate |
2020 |
url |
http://hdl.handle.net/11122/12305 |
geographic |
Arctic Fairbanks |
geographic_facet |
Arctic Fairbanks |
genre |
Arctic Alaska |
genre_facet |
Arctic Alaska |
op_relation |
http://hdl.handle.net/11122/12305 Department of Electrical and Computer Engineering |
_version_ |
1766335705042124800 |