# Projected Wind Energy Maximum Potential in Lithuania
## 2 Methodology
### Energy Analysis  
The resolution used in the models is usually too rough (-70-400 km) to be used for the comparison of meteorological observations and projected data [37]. Every model has a different resolution. For example, IPSL-CM5A-MR's resolution is 1.9\({}^{\circ}\)\(\times\) 3.75\({}^{\circ}\). As projected wind speed data cannot usually be extracted for the desired point, the closest grid point was found, and the data were extracted. Wind potential evaluation models require finer-scale climate data to assess wind speed trends induced by climate change. Downscaling is required in any impact studies due to varying agricultural and natural landscapes across small distances [37]. Therefore, downscaling was performed using the Inverse Distance Weighted (IDW) interpolation method. After both observed and projected wind speed data had been collected, bias adjustment was performed. Bias adjustment is usually needed, as substantial biases are uncovered by comparing observed and projected wind speed data. The percentage change in wind speed from the reference period of 2015-2020 was calculated for every year until the end of the century using the equation below:  
\[a_{i}=\frac{\left(RF_{p}-ws_{i}\right)\cdot 100}{RF_{p}} \tag{1}\]  
where \(a_{i}\) is the projected annual wind speed change (\(i\) represents the day since the start of the observations) in %, \(RF_{p}\) is the mean wind speed over the reference period using projected data in m/s and \(ws_{i}\) is the projected annual mean wind speed (i represents day since the start of the observations) in m/s. After the conversion of wind speed to a percentage is performed, the projected wind speed was calculated using the historical data on average wind speed, which were obtained for the same period of 2015-2020. The equation below shows how projected wind speed is calculated:  
\[w_{i}=\frac{\left(100-a_{i}\right)\cdot RF_{o}}{100} \tag{2}\]  
where \(w_{i}\) is the expected annual wind speed (\(i\) represents the day since the start of the observations) in m/s, and \(RF_{o}\) is the mean wind speed over the reference period [38]. Wind speed is usually measured at the height of 2 m or 10 m at meteorological stations. The data used in this study, both historical and projected, are presented at 10 m. However, the most common wind turbine heights vary between 100 m and 120 m [21; 39]. Therefore, for \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Model** & **Institution** & **Country** & **Horizontal Resolution** \\ \hline MPI-ESM-LR & Max Planck Institute for Meteorology Earth System & Germany & 1.875\({}^{\circ}\)\(\times\) 1.875\({}^{\circ}\) \\ HadGem2-ES & Hadley Centre Global Environmental Model & United Kingdom & 1.25\({}^{\circ}\)\(\times\) 1.875\({}^{\circ}\) \\ IPSL-CM5A-MR & Institute Pierre Simon Laplace & France & 1.9\({}^{\circ}\)\(\times\) 3.75\({}^{\circ}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Models used in this research. a proper assessment of the wind speed potential, the near-surface wind speed is converted to the average height of the wind turbines (100 m in this study) using the following equation:  
\[V(h)=V(h_{0})\cdot\left(\frac{h}{h_{0}}\right)^{\infty} \tag{3}\]  
where \(V(h)\)--wind speed at the specified height, m/s; \(V(h_{0})\)--near-surface wind speed, m/s; \(h\)--specified height, m; \(h_{0}\) --near-surface height, m; \(\alpha\)--wind shear exponent, 1/7, in this study [40]. Wind potential calculations are based on realizable wind turbine installations using wind speed conversion to energy. This has been performed using the equation below [41]. \[P=\frac{1}{2}C_{p}\rho AV^{3} \tag{4}\]  
where \(P\)--wind potential, W; \(C_{\text{p}}\)--power coefficient of a turbine (dimensionless); \(\rho\)--air density (1.225 kg/m\({}^{3}\) is the standard value, which is assumed in this study [21]); \(A\)--rotor swept area, m\({}^{2}\); V--wind speed, m/s. [PERSON] et al.