Intelligent Control of Ventilation System for Energy-Efficient Buildings With CO2 Predictive Model

In this paper, an intelligent control strategy for ventilation systems in energy-efficient buildings is proposed. The design goal of the intelligent controller is to determine the optimal ventilation rate efficiently and accurately by maintaining the indoor CO2 concentration in the comfort zone with a reduced amount of energy consumption. In this study, the CO2 concentration is used as the indicator of human comfort in terms of indoor air quality. In addition, a CO2 predictive model is utilized to forecast the indoor CO2 concentration based on the occupancy pattern of buildings. Due to the high non-linearity of the model, particle swarm optimization (PSO) is applied to derive the optimal ventilation rate. Fuzzy technique is used to represent the relationship between the ventilation rate and the corresponding power consumption for mechanical ventilation systems. As compared with the traditional ON/OFF or fixed ventilation control scheme, the performance of the proposed intelligent control system has demonstrated its advantage in energy savings. Three case studies are analyzed in different situations and using different input parameters. The corresponding simulation results confirm the viability of the proposed intelligent control strategy for ventilation systems.