This study was per ㎡ apartments in renewable energy electricity saving measures were analyzed public. First, based on the results of multiple regression analysis of renewable energy per ㎡ apartments and analysis of public electricity-saving measures are as follows. The greater the number of households, the fewer the number of lifts, the more condominium, apartment hallway type more likely, a small number of years elapsed apartment (new apartment), the more electricity per unit area decreases the public was analyzed. Next, the hidden layer of the neural network analysis result, ㎡ party public electricity affects orientation is unknown. However, the accuracy of the model is high compared to the regression analysis, so take advantage of them when you can have a high predictive power. Neural network analysis of the relative influence of the independent variables are the size of Type of ownership>Corridor type>the uppermost stratum>the number of households>he number of Dong> the number of lifts>Heating Type>number of years>Administration Type.