James Menart, Ph.D. (Advisor); Rory Roberts, Ph.D. (Committee Member); Mitch Wolff, Ph.D. (Committee Member)
Master of Science in Renewable and Clean Energy Engineering (MSRCE)
At the present time, using wind and solar energy for producing electricity in the United States is becoming cost competitive. According to Lazard’s 2019  levelized cost of energy (LCOE) analysis of a number of energy sources used for producing electricity in the United States, wind and solar are cheaper than natural gas and coal. While capital, maintenance, operation, and fuel costs are included in LCOE numbers, energy source intermittency is not. Intermittency is an important issue with wind and solar energy sources, but not with natural gas or coal energy sources. Combining wind and solar energy sources into one electrical generating station, is one means by which the intermittency of the electricity provided by wind alone and solar alone can be reduced. The combination of wind turbines and solar photovoltaic panels into a wind-solar farm can produce electricity over a greater fraction of the day or year than wind or solar alone. Predicting the energy output of different combinations of wind turbines and solar panels in a wind-solar farm is an objective of this work. While yearly electricity production rates are an important and necessary part of this work, this quantity does not provide a means to compare the wind-solar farms to each other, to a pure wind farm, to a pure solar farm, or to meeting a given electrical demand by purchasing all electricity from the local electrical grid. An economic analysis has to be performed to do this. This is the ultimate objective of this work. The economic analysis done in this work determines the net present cost of providing a specified electricity demand by a wind-solar farm with grid backup. Including grid purchased electricity to meet demand that cannot be met by the wind-solar farm is essential in this economic analysis. This sets the net present cost of providing all the electricity demand by grid purchased electricity as the cost that must be beat by a wind-solar farm with grid backup. Using grid backup also ensures that all of the electrical demand is met. Doing the economic analysis this way, means the intermittency costs of wind and solar are included in the economic analysis. The electrical output of many combinations of wind turbines and solar panels into one wind-solar farm are simulated in this work to see which combination provides the lowest netiv present cost of electricity for a specified electrical demand. The net present cost analysis performed n this work is different than a LCOE analysis because all the electricity produced for the net present cost analysis does not have value. For most of the simulations in this work, excess generated electricity is given no value. Only one economic simulation, for a given location, performed in this work is allowed to sell excess electricity from the wind-solar farm back to the electrical grid; and this is done at half the price at which it is purchased. The mathematical models that were pieced together to perform this work are presented. Detailed models of the solar and wind resource are utilized. The conversion of solar energy into electricity by the solar panels is handled with a solar panel efficiency. The conversion of wind energy into electricity is handled with a wind turbine power curve. Demand profiles for a given location are obtained from those published on the internet. The net present cost analysis is done including the time value of money. A MATLAB program was written to obtain numerical results from the mathematical models brought together to simulate the performance and costs of a windsolar farm with gird backup. Many results are presented in this thesis for three different cities in the United States. These cities are Rio Vista, California, Dallas, Texas, and Dayton, Ohio. For each of these locations, electricity demand profiles, wind and solar resource profiles, electricity produced by different sizes of wind-solar farms, excess electricity produced by these wind-solar farms over the required demand, and the net present cost of these wind-solar farms with grid backup using different cost constraints are presented. A base case of costs is developed and then single changes to these base case costs are investigated. The results show that combining wind turbines with photovoltaic panels can reduce the cost of providing a specified electricity demand. In Rio Vista, California wind-solar farms are cost competitive, whereas in Dayton, Ohio they are not. Whether a windsolar farm is cost competitive in Dallas, Texas depends on the cost conditions. A key factor in determining the attractiveness of wind-solar farms under the conditions used in this study, is the cost of grid electricity
Year Degree Awarded
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