## 2 Methods
### Evaluation of PV Power Output in Candidate Sites  
The PV power output per capacity per hour data (unit: h) are normalized by dividing the PV power output into the PV capacity to minimize the bias caused by collecting from historical measurements in the low capacities. These data are obtained by estimating the monthly available solar power at a raster level, using the computational method of [11]. The training model for solar power generation is built based on terrain maps (i.e., DEM), solar irradiation, temperature, wind speed, and precipitation: terrain maps were used to consider the effect of reducing solar radiation (e.g., shadow effect) reaching the target terrain by adjacent terrain, solar irradiation (e.g., direct beam, diffuse-sky radiation) that estimates in tilted surfaces generated from terrain maps such as slope and aspect information was used as a major energy source for solar power generation, and three weather components are used to reflect the constantly changing weather requirements. In short, their method used map-type data to consider the meteorological and geographical characteristics of a region adjacent to the PV plant. Their forecasting model achieved a mean absolute percent error (MAPE) of 8.639%. Between January 2013 and March 2018, the estimation model showed the best performance in March 2017 (i.e., a MAPE of 5.350%). Thus, this study proceeds with the site  
Figure 3: Computational geo-spatial analysis process for selecting sites near highway networks; (**a**) existing national highway in South Korea, (**b**) restriction conditions of the distance to highway networks (<200 m), (**c**) restriction conditions of non-installable areas (e.g., river, reservoir, higher slope), and (**d**) the result of constrained regions by spatial analysis in the case area. selection by computing the PV power output (unit of MWh) from the map showing the estimated PV power output per capacity per hour between January and December 2017. The PV power output is calculated by multiplying the PV capacity (i.e., unit of MW) by the power generation per unit capacity per hour (i.e., unit of h). To obtain information on the PV capacity, the number of panels installed in the candidate area (i.e., 30 \(\times\) 30 m\({}^{2}\)) is multiplied by the standard capacity of one solar panel (Figure 4a). As shown in Figure 4d, the number of installed panels is computed by multiplying the number of vertical installations (i.e., 30 m/width of solar panels (W) in Figure 4a) by the number of horizontal installations (i.e., 30 m/separation distance (d) in Figure 4b,c). For example, as shown in Figure 4a, this study assumed that a solar panel has a capacity of 400 W, a width of 1.024 m (W), and a height of 2.024 m (L). Then, the horizontal separation distance (d) (Figure 4b,c) in the study-area region (37.474\({}^{\circ}\) north latitude) can be calculated as 3.75 m, using Equation (1). However, because all candidate sites have gradients, the separation distance is adjusted by considering the gradient (d' = 4.471 m), as shown in Equation (2). \[\text{d}=\text{L}\ \times\ [\text{cos(a)}+\text{sin(a)}\ \times\ \text{tan(latitude}+23.5^{\circ})] \tag{1}\]  
\[\text{d'}=\text{d}\ \times\ \text{sec(c)}, \tag{2}\]  
where d is the separation distance, L is the vertical length of a single panel, a (\({}^{\circ}\)) is the angle between the panel and the horizontal surface, c (\({}^{\circ}\)) is the gradient of the tilted surface, and d' is the adjusted separation distance from d for considering the gradient. As a result, the total solar installation capacity in the study area was 210 solar panels, and the PV output capacity installed in 30 \(\times\) 30 m\({}^{2}\) is 0.084 MWh. Figure 4: Illustration of computing the solar PV output capacity; (**a**) the size of a solar panel used in this study, (**b**) computation of separation from horizontal surfaces, (**c**) computation of separation from tilted surfaces, and (**d**) solar PV power-plant capacity at one raster pixel from the PV power-output map in the study area (Ucheon-myeon).