## 2 Materials and Methods
### Final Design Characteristics
#### 2.4.4 Net Capacity Factor  
The maximum capacity of the wind turbine is theorized to be only able to capture 0.59% of the total kinetic energy of the wind. The Theory, better known as the Betz limit,  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Wind Plant Characteristics Associated with Average Wind Speed**} \\ \hline Average Annual Wind Speed at 80 m & \(\leq\)5.5 & 7.40 & 8.0 & 8.4 & \(\geq\)10.0 \\ Hub Height (m/s) & 200 & 237 & 245 & 255 & 325 \\ Specific Power (W/m\({}^{2}\)) & 2 & 2 & 2 & 2 & 2 \\ Machine Rating (MW) & 2 & 2 & 2 & 2 & 2 \\ Rotor Diameter (m) & 113 & 104 & 102.0 & 100 & 89 \\ Hub Height (m) & 80 & 80 & 80 & 80 & 80 \\ CAPEX (\(\ell\)/kW) & 1.303 & 1.242 & 1.232 & 1.219 & 1.156 \\ OPEX (\(\ell\)/kW/year) & 38.3 & 38.3 & 38.3 & 38.3 & 38.3 \\ Capacity Factor * & 27\% & 39\% & 43\% & 45\% & 49\% \\ FCR (real) [Real WACC \({}^{\ddagger}\) = 5.7\%] & 9.6\% & 9.6\% & 9.6\% & 9.6\% \\ LCOE (\(\ell\)/MWh) & 69.9 & 45.8 & 41.3 & 39.8 & 35.3 \\ \hline \hline \end{tabular}  
* Capacity factor estimated using the annual average wind speed, Weibull distribution with K = 2, and losses including availability of 16.7%. \({}^{\ddagger}\) Weighted Average Cost of Capital (WACC). Please note that the table was adopted from the original source which is in USD and the monetary values have been converted to GBP from USD where the conversion rate GBP1 = USD1.331 was used.  
\end{table}
Table 2: BEIS Pure LCOE [17].  
Figure 1: Scotland’s mean annual wind speed [18].  
stands true. Entailing associated losses can be attributed to turbine design or wind resource characteristics [17], the net generational performance slips further when additional effects such as array wake losses, environmental aspects, transmission losses and blade soiling losses are accounted for [17]. According to [19], historical net capacity figures lie in the region of 28.5% to 49.5%. However, [19] suggests that load factors for 13-15 MW turbines may reach as high 51-53%, depending on location.  
Weaknesses associated with AEP calculation are the exclusion of degradation and downtime loss from maintenance and repair. Both NREL and BEIS do not account for either factor within both calculations.  
Performance degradation from age affects all wind farms, no matter the generation of turbine. As such, any decrease in performance would raise the levelised cost of electricity. According to [20] \"wind turbines are found to lose 1.6 \(\pm\) 0.2% of their output per year\", resulting in a net increase LCOE valuation of 9% over a 20-year period.  
Currently the total number of expected days the turbine will be realistically operational is not factored into the BEIS LCOE calculation, thus the total generational capacity currently represents 8760 hours of operation every year for the expected service life of the turbine. An analysis by [21] estimated the net availability from a Dutch offshore windfarm located 35 km of the coast ranged from 85% to 94% due to maintenance and repair.  
Gathering accurate and certifiable data surrounding these factors is strenuous at best without the help of contracting offshore support companies. Using justifiable assumptions can mitigate this effect into a generalized net capacity factor. The net capacity factor will be used to adjust the nameplate capacity to the appropriate rate based on low, mid, and high scenarios.  
A sensitivity analysis in Case Study B examines the extent the expected net capacity factor has upon the LCOE calculations across all three calculators: BEIS, Fixed and floating.