Energy consumption modelling analysis of prefabricated buildings based on KPCA-WL SSVM

Abstract

The energy consumption of prefabricated buildings under multi-layer building materials system is affected by different weight factors. In order to improve the level of energy consumption prediction, a method of energy consumption prediction of prefabricated buildings under multi-layer building materials system based on KPCA - WL SSVM is proposed. Taking indoor ambient temperature, lighting conditions, utilization rate of electric facilities, etc. as the combined weight of assembled building energy consumption under multi-layer building materials system structure, the energy consumption simulation and energy con?sumption allocation model of assembled building under multi-layer building materials system structure controlled by multi-component energy consumption parameter support vector machine is established, and the support vector machine based on KPCA - WL SSVM and principal component analysis dynamic fitting method are adopted. The energy consumption parameters of prefabricated buildings under multi-layer building materials system structure are detected and estimated, and the energy consumption patterns, energy consumption distribu?tion with different characteristics and energy consumption prediction model parameters of prefabricated buildings under multi-layer building materials system structure are obtained. Then, the emission factor and power consumption factor prediction model of prefabricated buildings under multi-layer building materials system structure is established, and the dynamic prediction and evaluation of energy consumption of prefabricated buildings under multi-layer building materials system structure are realized. The test results show that the fitting degree of energy consumption prediction of prefabricated buildings under multi-layer building material system structure is high, the model optimization design of energy consumption of prefabricated buildings is realized, the prediction accuracy of building energy consumption is good, and the energy consumption can be effectively reduced.