| Title |
Spatio-temporal Interpolation to Estimate Temperature on Target Site with Kalman Filter |
| DOI |
https://doi.org/10.5573/ieie.2023.60.4.65 |
| Keywords |
Spatial interpolation; Interpolation; Kalman filter; Estimation; Temperature |
| Abstract |
On site climate data in new renewable energy facilities is essential information for an accurate prediction of power production. The on site data is able to estimate with recordings in its neighbors instead of operating extra weather stations. This paper proposes a novel spatial interpolation method incorporating Kalman filter to estimate temperature on target site. The proposed method consists of Kriging that estimates temperature based on spatial information by neighboring stations and Kalman filter that smooths the estimate by Kriging. With this framework, it improves the accuracy of estimation by integrating spatio-temporal information. In experiment with climate data collected in Gangneung and its neighbor for one year (Jan. 1st, 2022 ~ Dec. 31st, 2022), the proposed method shows improvement in accuracy of estimation compared to conventional methods. |