| Title |
Prediction of Building Power Consumption in the Short-Term through Solar Radiation Calculation Based on Ultra-short weather Forecast Data |
| Authors |
Yusun Ahn ; Yong-jun Lee ; Eun Joo Oh ; Byungseon sean Kim |
| DOI |
https://doi.org/10.6110/KJACR.2021.33.3.113 |
| Keywords |
기상 예보; 건물 전력 소비량; 태양 일사량; 기계 학습; 예측 Weather forecast; Building power consumption; Solar radiation; Machine learning; Prediction |
| Abstract |
With recent development of new and renewable systems and data processing technology, attention is being focused on the development of microgrid technology. One of key technologies of energy sharing is the prediction of power consumption of buildings for promoting economic and efficient energy use by providing decision making when sharing energy. Currently, studies that predict actual building power consumption by applying changed ultra-short weather forecast data from the Korea Meteorological Administration are insufficient. Studies that calculate and predict solar radiation without additional equipment are also insufficient. This study aims to predict power consumption of various buildings based on only meteorological data provided by the Korea Meteorological Administration. It is meaningful in that no additional devices are installed except for the power consumption data. Hourly solar radiation was derived using calculation formula. Accuracy was derived by applying meteorological data and calculated insolation as input data for predicting building power consumption. Solar radiation was derived with CVRMSE of 27.61%, MBE of -10.62%, and RMSE of 53.41 W/㎡ regarding the accuracy of calculated and measured data. Results of predicting building power consumption by applying input data to actual four buildings are presented by THE ASHRAE Guideline. They were found to fit the accuracy criterion. |