| Keywords |
Inverce distance weighted method; Photovoltaic system; Power output prediction; Spatial statistics |
| Abstract |
To predict the output of a photovoltaic system and efficiently manage it, it is essential to collect information on environmental variables such as solar radiation, temperature, cloudiness, etc. If it is impossible to collect information on environmental variables at the target location and public measurement stations are located far away, information can be interpolated using spatial statistical analysis. Spatial statistics techniques can predict location variables without existing data, but the prediction performance depends on the density or distance of the station used for analysis, the resolution of the grid, or the cell size. Therefore, in this study, solar radiation was predicted by the inverse distance weighted(IDW) interpolation method, and the amount of power generated by the PV system in operation was estimated using the predicted insolation information. In addition, the effect of the minimum distance of the station and the cell size of the grid on the prediction of solar radiation and power output was analyzed. As a result, The prediction performance using the IDW was analyzed to be relatively accurate when the minimum distance of the observation station was about 25km. However, the correlation of prediction accuracy according to the minimum distance to the station was not observed. The cell size of spatial interpolation also affected the accuracy, with up to 53.2% improvement in accuracy when the cell size was above 50,000m compared to below 50,000m. |