# Heat loss evaluation for heating building envelope based on relevance vector machine

## TL;DR

This paper introduces a new method using the relevance vector machine to evaluate heat loss in building envelopes, improving accuracy compared to existing models.

## Contribution

A novel heat loss evaluation method using the relevance vector machine (RVM) regression model is proposed.

## Key findings

- The RVM regression model outperformed response surface methodology and support vector machine models in heat loss evaluation.
- The RVM-based method established dynamic temperature baselines for different energy-saving standards in building envelopes.
- The method identified significant heat loss in a residential building, with 87% of points exceeding temperature baselines by over 2°C.

## Abstract

Due to the influence of many factors, there is no reasonable evaluation method for the heat loss evaluation of the envelope, which leads to the deviation of the evaluation results of building energy consumption. By comparing different regression analysis models and considering the heat transfer characteristics of the envelope and heat loss evaluation needs, the dynamic reference value of heat loss evaluation “temperature baseline” which meets different energy saving standards is established. The evaluation method of instantaneous heat loss of the envelope is proposed and the heat loss is studied. The results showed that the performance indexes of relevance vector machine (RVM) regression model was superior to the other two regression models(response surface methodology (RSM), support vector machine (SVM). Based on the RVM regression model, the dynamic prediction model of “temperature baseline” was established by combining numerical simulation with regression analysis. Taking a residential building as an example, the envelope temperature baselines meeting the energy saving standard of 75% and 50% were obtained by using the prediction model, the temperature baselines of walls and windows that save 75% energy were −0.6°C and 1.9 °C respectively, and those that save 50% energy were 1.2°C and 4.5°C. The infrared image and heat loss evaluation method found that 87% of the points exceeded the temperature baseline by more than 2°C, and the total heat loss of the wall with an area of 13m2 was 471W. The heat loss evaluation method based on RVM proposed in this paper can objectively evaluate the heat loss of building.