# A Feature-Based Cost Estimation Model for Wind Turbine Blade Spar Caps
## 5 Summary  
The market for wind energy is increasingly competitive as electricity prices fall. Existing cost models focus on entire wind turbine systems. However, system-level design and complete turbine replacement are very expensive strategies for lowering Levelized Cost of Energy (LCOE). Another issue is the environmental cost of increased material consumption. Consequently, turbine manufacturers are starting to focus on the feasibility of retrofitting existing turbine designs with longer CFRP spar cap blades to extend wind turbine life.  
A cost model was developed to assess the commercial feasibility of retrofitting same length turbine glass and longer length carbon fiber blades in the 35 to 75 m range. Tooling and capital cost data were unavailable for blades lengths 40 to 75 m. A wind turbine blade manufacturer supplied cost data for a 10 m spar cap analogue part, termed a Reference Standard, made from either glass or carbon fiber composite, and a 35 m blade box spar cap, termed a Calibration Standard. Glass and carbon fiber composite mass data for a box spar cap design was obtained from a cost and engineering study of spar caps in the 35 to 75 m spar cap range. A technical cost modelling (TCM) approach was employed, in  
Figure 11: Decrease in percentage reduction for LCOE at two CFRP prices.  
which cost scales with features defined as mass, volume fraction, and complexity to derive tooling and capital cost data for spar cap lengths 40 to 75 m. In TCM, cost resources can be approximate and isolated, giving the model flexibility, scalability, and adaptability. As more data becomes available, detail can be added to improve predictive power.  
Data was generated by the model to derive cost curves for GFRP and CFRP composite spar caps from 35 to 75 m blade length with annual production rates of 285 and 272 parts, respectively. Cost Scaling Feature Factors incorporating Cost Factor Indices derived from material, reference, and calibration cost data were developed to predict how spar cap costs such as dedicated tooling scale with part features. The only feature varied was part mass, with volume fraction and part complexity remaining constant. For both CFRP and GFRP, material and direct labor costs increase as a proportion of total cost from 35 to 75 m, while indirect labor, capital, tooling, and utilities decrease. GFRP and CFRP cost curves were compared with independent cost data from a manufacturer for a box spar turbine blade design in 35 to 75 m blade lengths.  
For CFRP, the average variation was 6.8% between the model and manufacturer's cost, while for GFRP the variation was 20.5%. An expression was introduced relating organizational learning to manufacturing complexity. If direct labor cost is assumed greater for heavier GFRP compared with CFRP by a manufacturing complexity factor of 4, the variation is 8.6%. For a part in which detailed cost data is not known, a rough order of magnitute (ROM) estimation of costs that is within 20% of the expected cost is deemed acceptable. Therefore, based on the cost data provided and asuumptions adopted, the model is considered validated.  
The cost of same length retrofit GFRP spar cap blades and 3 m longer CFRP blades was taken from the cost curve. Using precalculated turbine investment, operational and maintenance costs, and power generation data for a 20-year lifetime, LCOE was calculated for 20-year baseline GFRP blade turbines ranging from 35 to 75 m. LCOE for GFRP and CFRP turbine retrofits was then calculated and compared by inserting model-derived retrofit costs. Sensitivity analysis for one variable, CFRP material cost, was performed for blade retrofit feasibility. LCOE reduction for longer length CFRP retrofits compared with same length GFRP retrofits decreased as blade length increased, implying that at some blade length above 75 m, CFRP retrofits may not be viable. Lower CFRP prices will increase CFRP retrofit viability at longer blade lengths.