Energy Consumption Supervision Model Research In Campus Energy-saving Supervision Platform Based On Data Mining

Colleges and universities are not only an important component of the society, but also a major consumer of the energy and resources. Their energy consumption of different sorts features rich varieties, large total volume, and huge potentials in saving energy, which has made energy conservation and emission reduction of the colleges and universities a significant content in that work of the society. At the same time, carrying out the work of energy-conserving supervision in colleges and universities is the demand of realizing the energy-conserving supervision of colleges as well as a means to deepen the concept of building a resource-saving and environmental-friendly society in the minds of students, which actually has a profound meaning. In recent years, some colleges and universities have responded actively to the country’s call to fully carry out the construction of a conservation-minded campus. However, with different understandings and awareness to the economical campus, the campuses should be built in accordance with their own characteristics. The construction of energy-saving supervision platform can realize detection, statistics, analysis and regulation of the campus’ energy consumption. Then, according to the results of statistical analysis, one could make an energy-conserving and emission-reducing plan to reduce the energy waste and to provide reliable data support and effective solutions to the further improvement of schools’resource utilization rate and energy-saving management level.Based on the energy-saving supervision platform of Anhui University, this paper mainly introduces the backgrounds and significance of that platforms’ construction of colleges and universities, and also expounds the current research states of building conservation-minded campus and its current building states of Anhui University, putting emphasis on classification statistics of the campus’s energy consumption and statistical analysis to its buildings and departments by the day, the month and the year. Energy-saving supervision platform has developed and designed different modules, including foundation platform subsystem, data acquisition subsystem, electricity detection subsystem, water supply pipe network monitoring subsystem, energy comprehensive analysis subsystem, energy plan indicators management, early warning of energy consumption and public notification.In the process of data processing, in view of the large amount of data in the later stage and in order to improve the accuracy of the data, we would clean the original data. And ruling out the influence of dirty data by implementing energy consumption statistics on the data cleaned. After the statistical analysis of energy-consumption characteristics of campus and energy consumption of buildings, this paper puts forward the campus building’s energy consumption supervision model based on data mining technology, which focused on addressing the shortcomings of existing supervision methods. Firstly, setting up an energy-consuming pattern discrimination tree through the clustering recognition of energy consumption’s historical data to obtain the energy consumption models. Then doing pattern matching for real-time energy consumption of buildings, and carrying out outlier analysis for those, who have the same energy consumption model with the historical data. After that, judging whether they are abnormal energy consumptions as per the results of outlier analysis. Finally, giving specific instruction by taking a certain office building’s use of energy-saving supervision model in the campus as an example.