Cost-of-energy Optimization of 3D Printed Small-scale Wind Turbine Blades
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Date
2024-06
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Addis Ababa University
Abstract
Human-induced climate change is an urgent challenge that necessitates the adoption of renewable energy sources. Wind energy conversion proves to be a promising option, with the horizontal axis wind turbines being identified as the most efficient and mature technology. While large turbines have been widely explored, there is a need for small-scale power solutions – notably in Ethiopia given its low electrification rate. The optimization of wind turbines is a well researched topic, but cost-of-energy optimization has been a challenge due to the difficulty in modeling the cost of traditional wind turbine manufacturing techniques. This research explores the use of 3D printing cost models to optimize energy costs in small-scale wind turbine blades. The cost involved in 3d printing a small wind turbine blade are explored. The cost of each activity in the process is modeled and a total cost estimate is stipulated. A linear relationship was found between the volume of the blade and the turbine cost. This relationship was used in the cost-of-energy optimization of the blade. A python code utilizing a genetic algorithm and a blade element momentum analysis model is written and utilized to obtain a cost-of-energy optimized design. The design variables chosen for optimization are the design wind speed, the tip-speed ratio and the airfoils used. The wind distribution was taken to be that of Addis Ababa. The results indicate the great potential of direct cost-of-energy optimization. A cost of energy of 0.67 $/KWh is obtained for the design which is better than the Skystream 3.7 wind turbine for our location. Sensitivity analysis is also performed by varying the design variables. The objective was found to be much more sensitive to the tip-speed ratio than the design wind speed.
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Keywords
small wind turbines, cost-of-energy optimization, 3D printing, genetic algorithm, cost modeling