Development of a Techno-Economic Model to Explore Wind Blade Manufacturing Options [Tech Paper]

Thursday, September 26 8:00 AM - 8:25 AM

Location: Convention Center I 210D

Session Information

Title: Development of a Techno-Economic Model to Explore Wind Blade Manufacturing Options [Tech Paper]


 For wind to continue to increase its share of the U.S. electrical-power portfolio, and to be competitive with other modes of generating electricity, the stakeholders along the wind turbine supply chain are continuously looking for ways to the reduce the levelized cost of electricity (LCOE) from wind turbines.  Wind blades are a prime candidate for cost reduction because they are one of the most expensive components on a wind turbine, and one of the prime determinants of how much energy a turbine generates.    However, minimal automation has been adopted in the wind blade manufacturing industry, and a key cause has been the lack high-fidelity tools which can accurately model the full product life-cycle costs to demonstrate an acceptable ROI (Return on Investment). 
The costing models that exist today are based on academic studies and industry analyses which are out of date and in some cases use data drawn from non-wind composites manufacturing.  As a result of not having access to a robust cost model, wind blade manufacturers are reluctant to invest in new processing technologies, and this has been compounded by an industry well aware of past failed investments in new wind blade automation.
This current research is addressing the need for better cost modeling by delivering a cost modeling tool which better captures all the costs of wind blade manufacturing versus what is currently available, and enables the confident prediction on the economic value of large manufacturing process changes.  This  paper presents the results to date in collecting data from industry and incorporating the data into a non-proprietary state-of-the-art model capable of directly incorporating user blades designs to generate costs based on parametric design factors and generic or user specific material, labor, and process data.  More importantly, explicit consideration is given to product life-cycle factors such as product life, startup and shutdown costs, and the production learning curve impact on multi-year cash flows.

Type: Manufacturing & Processing Technologies Conference Track