Control and Optimization of Indoor Environmental Quality Based on Model Prediction in Building

摘要

Control and optimization of the quality of the indoor environment are necessary to ensure indoor comfort and reduce building energy consumption. Indoor environmental quality that contains a variety of uncertainties and nonlinear factors is difficult to be described by the traditional linear system. In this paper, by defining the linear relationship between physical parameters and control parameters of the indoor environmental quality, the control, and energy consumption optimization modeling is established according to the data measured based on a bilinear model. On this basis, this study proposes a model predictive control system coupled with an intelligent optimizer for indoor environmental quality control. Ant colony optimization (ACO) is utilized to optimize the building energy management. Experimental results show that the proposed intelligent control system successfully manages indoor environmental quality and energy conservation.