Research on Regional Air Conditioning Temperature Energy Consumption Model Based on Regression Analysis

Abstract

With the increasing improvement of people's living standards, air conditioning as a major energy user has become an important factor affecting household electricity consumption plans. This study first identifies a strong correlation between temperature and air conditioning electricity consumption. Then, a regional air conditioning energy consumption model is developed based on regression analysis to meet the needs of household electricity management systems. First, to obtain a more intuitive relationship between temperature and electricity consumption, an improved k-means clustering algorithm is used to classify regional air conditioning energy consumption data. Second, based on four types of curves obtained by clustering, regression methods are used to propose a multi-class regional air conditioning energy consumption model which can support accurate quantitative analysis. Finally, the validity and accuracy of the proposed model are demonstrated by regional prediction experiments. The results can provide references for scientific electricity consumption planning of households.