Modeling and analysis of masonry electro-thermal heating and storage for optimal integration with remote stand-alone wind-diesel systems

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Author
Sateriale, Maura Eileen
Chair
Peterson, Rorik
Wies, Richard
Committee
Kim, Sun Woo
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URI
http://hdl.handle.net/11122/4476
Abstract
Due to their remote locations and small populations, many remote villages in Alaska generate electricity with microgrids that employ diesel-electric generators for their primary source of power, and supplement this production with wind turbines. In such communities, it is economically advantageous to minimize fuel consumption by shifting as much of the village's energy demands to the wind system as is feasible. When wind turbines produce in excess of the demand, it is possible to use the excess electricity to power resistance heaters to heat water in tanks or masonry. The heat is then stored so that it can be used immediately or in the future to meet the village's heating demand. This is called electrothermal heating (ETH). The goal of this research work is to use MATLAB/Simulink� to model heating scenarios employing masonry electrothermal heaters to investigate how excess electricity from wind can be used for immediate heating needs and storage. The results demonstrate reduced heating oil consumption using electrothermal heating and increased storage potential in conjunction with oil stoves.
Description
Thesis (M.S.) University of Alaska Fairbanks, 2013
Table of Contents
Chapter 1: Introduction -- 1.1. Introduction -- 1.2. Background -- 1.2.1. Kongiganak -- 1.2.2. Unalakleet -- 1.3. ETH in wind-diesel systems -- 1.3.1. Heating -- 1.3.2. Combined heat and power -- 1.3.3. Displacing heating fuel -- 1.4. Methods of Heating and Thermal Energy Storage (TES) -- 1.4.1. ETH in water tanks -- 1.4.2. ETH with masonry bricks -- 1.5. ETH model with MATLAB/Simulink� -- Chapter 2: Electrothermal and oil heating model theory -- 2.1. Components of the system -- 2.1.1. ETH masonry heaters -- 2.1.2. Oil heating stoves -- 2.1.3. Building models -- 2.1.4. Hot water heaters -- 2.2. Buildings, facilities and heating sources -- 2.2.1. Community buildings and heating sources -- 2.2.1.2. Kongiganak -- 2.2.1.2. Unalakleet -- 2.3. Wind resources -- 2.3.1. Kongiganak wind resources -- 2.3.2. Unalakleet wind resources -- 2.3.3. Weibull distribution -- 2.3.3.1. Weibull distribution for wind speed in Kongiganak -- 2.3.3.2. Weibull distribution for wind speed in Unalakleet -- 2.3.4. Wind power -- 2.4. Electrical power resources -- 2.4.1. Kongiganak -- 2.4.2. Unalakleet -- 2.5. Ambient temperature profiles -- 2.5.1. Temperature in Kongiganak -- 2.5.2. Temperature in Unalakleet -- 2.6. Parameters used for economic evaluation -- 2.6.1. Investment rate, inflation rate, and discount rate -- 2.6.2. Net present value -- 2.6.4. Payback period -- 2.6.5. Cost of energy -- 2.7. Summary of heat and energy transfer model theory -- Chapter 3: Modeling and verification of masonry ETH in Simulink� -- Chapter 3: Modeling and verification of masonry ETH in Simulink� -- 3.1. House thermal energy model -- 3.2. Oil heater model -- 3.3. Steffes heater model -- 3.3.1. Modeling the daily temperature demand -- 3.4. Modeling electric generation sources -- 3.5. Wind turbines -- 3.6. Modeling systems -- 3.6.1. Heater loses heat to house of constant temperature -- 3.6.2. Heater loses heat to perfectly insulated house -- 3.6.3. Heater in very lossy environment -- 3.6.4. Steffes heater (with thermostat) charging in a very lossy environment -- 3.6.5. Steffes heater (with thermostat) discharging in a very lossy environment -- 3.6.6. Thermostatically controlled heater meets thermal demand for year -- 3.6.7. Small house -- 3.6.7.1. Small house in Kongiganak -- 3.6.7.2. Small house in Unalakleet -- 3.6.8. Bigger house -- 3.6.8.1. Bigger house in Kongiganak -- 3.6.8.2. Bigger house in Unalakleet -- 3.6.9. Community center -- 3.6.9.1. Community center in Kongiganak -- 3.6.9.2. Community center in unalakleet -- 3.6.10. Higher set point -- 3.6.11. Lower set point -- Chapter 4: Masonry electrothermal heating and storage scenarios -- 4.1. Annual simulations for different buildings and set points -- 4.2. Test cases -- 4.2.1. Case 1: Heating with Toyo stove -- 4.2.1.1. Kongiganak results for test case 1 -- 4.2.1.2. Unalakleet results for test case 1 -- 4.2.2. Case 2: Steffes heater powered by diesel electric generation -- 4.2.2.1. Kongiganak results for test case 2 -- 4.2.2.2. Unalakleet results for test case 2 -- 4.2.3. Case 3: Steffes heater powered from wind energy only -- 4.2.3.1. Case 3: Kongiganak -- 4.2.3.2. Case 3: Unalakleet -- 4.2.4. Case 4: Steffes powered from excess wind with Toyo stove for backup heat -- 4.2.4.1. Case 4: Kongiganak -- 4.2.4.2. Case 4: Unalakleet -- 4.2.5. Case 5: Steffes charge from excess wind and diesel electric generators -- 4.2.5.1. Case 5: Kongiganak -- 4.2.5.2. Case 5: Unalakleet -- 4.2.6. Summary -- 4.3. Results -- 4.3.1. Simple payback periods -- 4.4. Net present values -- 4.5. Evaluating the results -- 4.5.1. Evaluating Kongiganak -- 4.5.2. Evaluating Unalakleet -- 4.5.3. Re-evaluating the results with infrastructure changes -- Chapter 5: Summary, conclusions and future research -- 5.1. Summary -- 5.1.1. Kongiganak summary -- 5.1.2. Unalakleet summary -- 5.2. Effect of efficiencies on results -- 5.3. Effect of changing R-values on house heating -- 5.4. Model improvements -- 5.5. Future research -- References -- Appendix.
Date
2013-12
Type
Thesis
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