| Title |
A Study on Daily Precooling Set-point Temperature Optimization for Reducing Peak Electric Power of an Office Building Using Genetic Algorithm |
| Authors |
Ki Beom Ku ; Shin Kyu Jeong |
| DOI |
https://doi.org/10.6110/KJACR.2022.34.1.042 |
| Keywords |
건물에너지; 피크전력; 예냉; 회귀모델; 유전알고리즘 Building energy; Peak electric power; Precooling; Regression model; Genetic algorithm |
| Abstract |
In this paper, the peak electric power of an office building was reduced with a precooling strategy. Precooling was conducted two hours before work time. Set-point temperatures for precooling were optimized using a genetic algorithm to minimize daily peak electric power. Searching for optimized set-point temperature was conducted with an objective function that was developed with a multiple regression model. The regression model used dry-bulb temperature, relative humidity, and the set-point temperature as the input parameters, and set daily peak power of the building as the output parameter. Model data were collected from ‘EnergyPlus’, a building energy simulation program. The applied building was ‘Medium Office’ provided by EnergyPlus. Based on our results, there was a 0.71~5.64% reduction in daily building peak power with the application of the optimized precooling setpoint temperature. In addition, the reduction of electricity cost due to the reduction of peak electric power was observed. |