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
Chair
Wies, RichardCommittee
Huang, DaisyAl-Badri, Maher
Keyword
Electric power distributionMicrogrids
Smart power grids
Renewable energy sources
Diesel electric power plants
Food security
Water security
Energy security
Electric power plants
Small power production facilities
Metadata
Show full item recordAbstract
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.Description
Thesis (M.S.) University of Alaska Fairbanks, 2020Table of Contents
1 Introduction -- 1.1 Problem statement -- 1.2 Food, energy, and water (FEW) interactions in remote Arctic microgrids of Alaska -- 1.3 Modeling approach for energy distribution models -- 1.4 Novelty of energy distribution models -- 1.5 Literature review -- 1.5.1 Existing FEW modeling approaches -- 1.5.2 Existing FEW modeling tools -- 1.6 Assessing renewable energy resources in Alaska -- 1.6.1 Plane of array solar irradiance -- 1.6.2 Wind resource -- 1.6.3 Hydropower resource -- 1.7 Renewable energy and hybrid systems modeling software tools -- 1.7.1 NREL PVWatts® -- 1.7.2 HOMER Pro® -- 1.8 Dispatchable loads -- 1.9 Thesis organization. 2 Energy requirements for on-grid FEW system loads -- 2.1 Energy flows in a greenhouse -- 2.1.1 Heat losses -- 2.1.2 Heat gains -- 2.1.3 Cooling requirements -- 2.1.4 Artificial lighting -- 2.2 Energy requirements for cold storage units -- 2.2.1 Transmission load -- 2.2.2 Infiltration load -- 2.2.3 Product heat load -- 2.2.4 Internal heat load -- 2.2.5 Vapor absorption refrigeration (VARC) system efficiency -- 2.2.6 Solar evacuated tubes -- 2.3 Energy requirements for community public water systems -- 2.3.1 Heating requirements -- 2.3.2 Modeling hourly electric load -- 2.4 Modular systems -- 2.4.1 UAA in-home water reuse system -- 2.4.2 The hydroponic cropbox -- 2.5 Summary of few energy requirements and loads. 3 Energy resource modeling, energy distribution, and model validations -- 3.1 Energy resource models -- 3.1.1 Solar PV model -- 3.1.2 Wind turbine generator model -- 3.1.3 Hydro model -- 3.1.4 Battery energy storage model -- 3.1.5 Diesel electric generator model -- 3.2 Energy distribution flow chart -- 3.2.1 Solar PV, wind, BESS, and diesel electric generator energy distribution analysis -- 3.2.2 Hydro, BESS, and diesel electric generator energy distribution analysis -- 3.3 Energy resource model validations -- 3.3.1 Solar PV model validation -- 3.3.2 Wind turbine generator model validation -- 3.3.3 Hydro model validation -- 3.3.4 diesel electric generator model validation -- 3.4 Model validation summary. 4 Case studies and results -- 4.1 Solar, wind, and hydro resource datasets -- 4.1.1 Solar irradiance and ambient temperatures -- 4.1.2 Wind speed -- 4.1.3 Power creek water flow rate -- 4.2 Energy distribution model assumptions and parameters -- 4.3 Energy-water and energy-food indices -- 4.3.1 Energy-water (EW) index -- 4.3.2 Energy-food (EF) index -- 4.4 Solar PV for Tanana's water treatment plant (WTP) and greenhouse system loads -- 4.4.1 Solar PV for WTP -- 4.4.2 Passive and active solar for Tanana's greenhouse -- 4.5 Solar PV and wind power for Kongiganak's water treatment plant (WTP) -- 4.6 Community cold storage unit -- 4.6.1 Calculating total load -- 4.6.2 Heat energy for vapor absorption refrigeration system -- 4.6.3 Electrical energy for a vapor compression refrigeration system -- 4.7 Cordova FEW analysis -- 4.7.1 Cordova's microgrid details -- 4.7.2 Electric load for Cordova's seafood processing plants -- 4.7.3 Available hydroelectric power at Power creek -- 4.7.4 Impacts of Battery Energy Storage System (BESS) on Cordova's microgrid -- 4.8 Summary of FEW simulation results and discussions. 5 Conclusion, future work, and lessons learned -- 5.1 Conclusion -- 5.2 Future work -- 5.3 Final thoughts -- References -- Appendix.Date
2020-08Type
ThesisCollections
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