Research on intelligent regulation of air conditioning energy saving based on human thermal comfort

Abstract

Air-conditioning system is the chief part of building energy consumption. With the global green energy initiative, reducing air conditioning energy consumption has great significance to the promotion of building energy conservation and emission reduce. Therefore, this paper proposes an energy saving control method for the air-conditioning of support vector regression (SVR) based on particle swarm optimization (PSO) to optimize energy consumption and thermal comfort, during the internal mechanism independent of air conditioning. In addition to the factors of indoor temperature, indoor humidity, outdoor temperature, outdoor humidity and thermal comfort constraints, the number and location distribution of people and the distribution of indoor heat load are also monitored. Intelligent adjustment according to the comfort level of human after all variables were imported into the intelligent system. In the experiment, a platform is built to evaluate the performance of the proposed method under various settings by the Computational Fluid Dynamics (CFD). The results show that the method can improve the accuracy of thermal comfort prediction and ensures that the energy consumption of air-conditioning is reduced while improving the thermal comfort of residents.