변풍량 공조시스템의 에너지 소비량 및 실내 온열환경의 최적 제어를 위한 알고리즘 개발

Abstract

The objective of this research is to suggest a method that can be used to obtain the optimal control set-point that considers weights of thermal comfort and heating, ventilation, and air conditioning (HVAC) energy consumption; this is done using a multi objective genetic algorithm. An artificial neural network is adopted in order to determine a prediction model for the thermal load, HVAC energy consumption and thermal comfort based on the properties of individual buildings. In this research, 64 building cases were simulated with EnergyPlus and OpenStudio to produce synthetic data. The simulation results of optimization showed that the control variables set, which saves 52% of the chiller energy with a small increase in PPD compared to the base case.