## 5 Discussion and Conclusions  
With the approach proposed in this study, it is possible to calculate the wind energy potential for a certain area using multiple points, which is superior to the single point-based wind energy potential determination studies [28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39] mentioned in the introduction section. In these point-based studies, wind energy potential calculations can only be made for these points and areal results cannot be produced. With the spatial interpolation method, which is a GIS function, wind speeds for an entire area can be generated by interpolating the wind speeds belonging to multiple points in a certain area. In this way, the total wind energy potential can be calculated for a study area using wind speeds. The wind speed maps of the Balikesir Province and its districts were produced using IDW, which is the most appropriate spatial interpolation method in this study. Area-based wind potentials of the study region were obtained for different ranges considering the wind turbine layout plan designed according to the national regulation. [PERSON] and [PERSON] [40] used the kriging interpolation method to obtain a wind speed map of the southern states of India. The produced wind speed map was insufficient in terms of cartographic representation. Another missing point in the study is that no comparison was made between interpolation methods. Likewise, [PERSON] et al. [41] also adopted the IDW interpolation method to generate a wind speed map of mainland China without comparing interpolation methods. The wind energy potential of the study area was determined by adopting the wind farm layout approach of [PERSON] [51] using wind potential calculation algorithms. These calculations were made according to the specifications of a specific wind turbine. Turbine specifications were used to obtain the maximum power coefficient in the study. [PERSON] et al. [42] used a GIS-based multi-criteria decision support system to determine the suitable areas for wind turbine installation in the western region of Iran. They used raw wind speed and roughness information via Wind atlas analysis and application program (WAsP) software and obtained a digital wind atlas. There was no information about interpolation methods and the process for creating the wind speed atlas in the study. A layout plan for the wind turbine installation was defined and the total wind energy potential was calculated for the study area. The number of wind turbines was given in the study, but no equations related to it were given. The total wind potential for a given wind turbine was determined. In this study, raw wind speeds gathered from TSMS stations were extrapolated to 100 m considering the roughness of the terrain, and wind speed maps were created using the IDW, kriging, natural neighbor, spline, and trend interpolation methods. The most appropriate method was determined to be IDW with the minimum RMSE value of 0.008 m/s. In addition, a layout plan for wind turbine installation was designed considering the minimum distances required between two turbines in the Regulation on the Technical Evaluation of Wind Source Based Electricity Generation Applications, and an equation (Equation (2)) was produced that gives the number of wind turbines that can be installed in a certain area in accordance with this layout plan. Unlike other studies carried out, no existing turbine model was taken as a reference, so that the model did not become dependent on any brand. Wind energy investors can apply this model with the parameters of the turbine model they want. Wind speeds and Equations (2) and (3) were used to calculate the wind energy potential for each wind speed range. Finally, the total wind energy potentials of the Balikesir Province and its districts were obtained by summing the wind energy potentials of all the ranges. When the threshold value for wind speed is taken as 6 m/s, the total wind power potential is calculated as 28,885.30 MW in the Balikesir Province.