Title :
Indoor air quality control for energy-efficient buildings using CO2 predictive model
Author :
Wang, Zhu ; Wang, Lingfeng
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Toledo, Toledo, OH, USA
Abstract :
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.
Keywords :
air pollution; building management systems; energy conservation; intelligent control; particle swarm optimisation; ventilation; CO2 predictive model; PSO; comfort zone; energy consumption; energy savings; energy-efficient buildings; indoor CO2 concentration; indoor air quality control; intelligent control system; optimal ventilation rate; particle swarm optimization; Buildings; Energy efficiency; Intelligent control; Particle swarm optimization; Predictive models; Ventilation; CO2 predictive model; Energy-efficient building; indoor air quality; intelligent control; particle swarm optimization;
Conference_Titel :
Industrial Informatics (INDIN), 2012 10th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-0312-5
DOI :
10.1109/INDIN.2012.6300925