# Systematic Analysis of Wind Resources for Eolic Potential in Bangladesh
## 4 Results and Discussions  
The results are analyzed for wind speed (m/s) and BLH (m), followed by wind power estimations. The boxplots in Figures 2 and 3 illustrate the descriptive statistics for the southern and northern regions, averaged from 1979 to 2018 and with a climate base period of 20 years (1979 to 2018). Figures 2a-d and 3a-d indicate the average wind speed and the anomalies for the southern regions. Here, Barishal (Figure 2a) experiences the highest \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Sample (N)** & **N = 45** & **N = 850** & **N = 880** & **N = 1005** & **N = 1110** \\ \hline Models and Regions & Bangladesh & South Asia & Papua New & Denmark; The & France; \\  & Divisions & Countries & Guinea & Netherlands & Germany \\ \hline Linear & 0.878 & 0.801 & 0.825 & 0.838 & 0.848 \\ \hline Exponential & 0.982 & 0.865 & 0.874 & 0.884 & 0.888 \\ \hline Polynomial & 0.985 & 0.892 & 0.911 & 0.906 & 0.911 \\ \hline Physical & 0.990 & 0.942 & 0.951 & 0.951 & 0.956 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Data sensitivity in modelling power estimations based on determination of coefficients. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**SPPM Name** & **Equation (Similar to Equations (1)–(3))** & **MAPE (\%)** & **RSE** \\ \hline Linear & \(P=132.78V-426.43\) & _58.03_ & _120.5_ \\ \hline Exponential & \(P=20.51e^{0.415V}\) & _22.92_ & _0.315_ \\ \hline Polynomial & \(P=0.2232V^{3}+10.984V^{2}-34.357V+60.641\) & _21.80_ & _92.69_ \\ \hline Physical & \(P=0.6V^{3}\) & _55.92_ \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summaries for SPPM mean absolute percentage and residual standard error (MAPE and RSE). of about 3.097, 3.565, 4.580, 4.772, and 4.665 (m/s), whereas Dhaka (Figure 2d) has the lowest speeds of about 1.589, 1.806, 3.283, 3.956, and 4.151 (m/s) increasing with the height from 10 to 250 m (converted from pressure levels from 1000 to 900 hPa). Moreover, Khulna (Figure 2b) and Chittagong (Figure 2c) stand quite neutral to the others with gentle speeds. For all cities in Southern region, variations in anomalies are found similar to each other (given in Figure 3a-d). To note, The northern regions show average wind speeds and anomalies for various heights in Figure 2e,f and Figure 3e,f, respectively. In the north, the lowest mean wind speed is found in Sylhet at about 1.094, 1.249, 2.093, 2.599, and 2.922 m/s and the highest is in Rajshahi at about 1.573, 2.007, 3.289, 3.583, and 3.637 m/s as the height increases. On the other hand, the anomalies for each city show similar variations in speed that are slightly increasing with the height (shown in Figure 3e-f). Figure 2: Descriptive statistics of wind speed (m/s) at 10 m and pressure levels: 1000, 975, 950, and 925 hPa for southern (top panels) and northern region (bottom panels) averaged from 1979 to 2018 with a climatic base of 20 years (1979 to 2000). The overall comparison in Bangladesh demonstrates that Sylhet is the weakest region (lowest speed), whereas Barishal is the strongest region (highest) for wind speed. The analysis for wind speed at various heights implies that mean wind speeds from 975 to 925 hPa (-80 to 200 m) are similar to each other. The mean wind speed is 4.3 and 3.3 m/s, respectively, for the southern and northern regions. Wind speeds and their anomalies provide evidence for an optimized height, i.e., 975 hPa (80 m), applicable (shown in Figure 4) in harnessing wind energy efficiently as there are no significant increasing or decreasing trends. For instance, anomalies for both regions are given in Figure 4a,c, which indicate the variations are close to each other for respective cities. However, there are few outliers particularly found for Khulna cities only in 2010 and 2015 that might have resulted because of tropical cyclones passing the region. As similar deviations were found in the  
Figure 3: Same as in Figure 2, but valid for anomalies of wind speed. range of \(-0.6\) to \(0.6\), these wind speeds meet the minimum threshold for turbine rotations.