The purpose of this study is to empirically analyze the effect of providing information on real-time district heating usage on energy saving for apartment complexes using a district heating system. Although Korea is an energy-guzzling country, it is a...
The purpose of this study is to empirically analyze the effect of providing information on real-time district heating usage on energy saving for apartment complexes using a district heating system. Although Korea is an energy-guzzling country, it is a country that relies on foreign resources that imports most of its resources. As a result, the issue of energy saving is a very important part in terms of energy security and national economy. The government has tried to solve this situation at various levels, but the effect is insignificant. Among various types of energy supply, in the case of district heating, it is more difficult to save energy due to the difficulty of replacing physical heating facilities and the fact that the energy-saving entity is the apartment management office, not the user.
In this study, a new approach to solving this problem is proposed. If the existing method of reducing district heating usage adopted the hardware improvement of the apartment machine room, this study proposes a software solution by improving end-user awareness. Specifically, it is an empirical study on the effectiveness of the method of inducing voluntary energy saving by allowing end users of each generation to recognize real-time district heating usage information.
As for the research method, among apartment complexes using district heating, apartment complexes that receive real-time usage information through a mobile app were selected as experimental groups, and apartment complexes under similar conditions were selected as control groups to compare their usage. For the experimental period, heating usage data for a total of two years, one year before and after the introduction of the mobile app, were used, and regression analysis was performed by applying the Difference-in-Differences (DID). In the regression analysis model, the intersection term was used to clearly show the effects of independent and control variables. The independent variable is whether or not real-time heating usage information is provided, and the dependent variable is selected as the heating usage of the unit area per hour. Since heating usage changes by 'climate factors', 'additional information provided', and 'change in lifestyle patterns', seasonal factors, monthly time points, and weekends and weekdays were selected as control variables. In addition, in order to control climatic conditions such as temperature, daily temperature difference, humidity, and wind speed as much as possible, a control group very similar to the experimental group was selected to increase the accuracy of the analysis.
As a result of regression analysis, it was found that the provision of real-time heating usage information had a statistically significant effect on heating usage reduction. However, the effect of information provision was significantly different depending on the season and whether on weekends or weekdays. In the analysis reflecting seasonal factors, the greatest saving effect was confirmed in winter. This is a period when there is a lot of room for usage reduction and interest in heating costs is high due to the seasonal characteristics of absolutely high heating usage, so the saving effect is considered to be excellent. As a control effect on weekdays and weekends reflecting life pattern factors, it was found that weekdays reduce heating usage more than weekends. In addition, the energy saving rate was calculated by analyzing the difference between the expected heating usage and the actual usage when real-time information was not provided.
This study is limited to existing electricity and water by conducting energy-saving effects by providing real-time information called direct feedback on energy products called district heating
It is significant in that it has expanded. It also suggested the possibility of further improvement in the future by seeking ways to further strengthen the effect of direct feedback through related theoretical background and prior research. The research results provide important implications for energy management and related policy making, and will also help improve the actual quality of life by contributing to reducing energy use and carbon emissions at the national level.