Indoor Air Quality Control for Energy-Efficient Buildings Using CO2 Predictive Model

摘要：

In this paper, an intelligent control system for indoor air quality in energy-efficient buildings is proposed. The goal of intelligent air quality control for energy-efficient buildings is to maintain the indoor CO2 concentration in the comfort zone with a minimum amount of energy consumption. In this study, the CO2 concentration is used as the indicator of indoor air quality and a CO2 predictive model is utilized to forecast the indoor CO2 concentration. Particle swarm optimization (PSO) is applied to derive the optimal ventilation rate. As compared with the traditional ON/OFF ventilation control system, the performance of the proposed intelligent control system has demonstrated its advantage in terms of energy savings. A case study and corresponding simulation results are detailed in the paper.

关键词： Energy-efficient building indoor air quality CO2 predictive model intelligent control particle swarm optimization

作者: Zhu Wang Lingfeng Wang

作者单位: Department of Electrical Engineering and Computer ScienceUniversity of ToledoToledo, OH, USA Department of Electrical Engineering and Computer Science University of Toledo Toledo, OH, USA

会议类型: 国际会议

会议名称: IEEE 10th International Conference on Industrial Informatics(第十届IEEE工业信息学国际学术会议 INDIN2012)

会议地点: 北京

会议语种:英文

页码: 133-138

在线出版日期: 2012-07-25（万方平台首次上网日期，不代表论文的发表时间）