| Title |
Load Forecasting Algorithm for Special Days by Considering Temperature Sensitivity and BTM Estimation |
| Authors |
권보성(Bo-Sung Kwon) ; 배동진(Dong-Jin Bae) ; 문찬호(Chan-Ho Moon) ; 송경빈(Kyung-Bin Song) |
| DOI |
https://doi.org/10.5370/KIEE.2021.70.2.290 |
| Keywords |
Behind-the-Meter Generation; Fuzzy Linear Regression; Short-Term Load Forecasting; Special Days |
| Abstract |
The load on the special days are relatively lower compared to load on normal days, the pattern of load is irregular, and the number of load data for the past similar days to the special day is limited. Since the load forecast error on special days is relatively large compared to the load forecast error on normal days, the improvement of load forecasting algorithm for special days is needed. An hourly load forecast algorithm for special days that can reflect the effect of temperature varying over time and the effect of BTM(Behind-the-Meter) solar photovoltaic(PV) generators increasing by year is developed to improve the load forecasting accuracy for special days. The proposed algorithm forecasts hourly load for special days using fuzzy linear regression, and then corrects the forecast load using both the temperature sensitivity and the estimated BTM solar PV generation. The forecast accuracy is improved when using the proposed algorithm to forecast the load on special days in 2019. |