Analysis And Research On Electric Consumption Characteristics Of College Students Based On Energy Management And Control System

With the development of the national smart grid,our government has become more and more demanding on the intelligent level of the power system,thus more and more attention is paid to the management and research of power consumers.At present,a large number of scholars have studied and analyzed the electricity consumption characteristics of residents,factories and other users.However,students are also an important and non-negligible group in the power consumers.It is of great significance to analyze the students’ electricity consumption characteristics.The study of students’ electrical characteristic curves and electricity consumption models has a huge impact on the research of user classification,load forecasting,load control,power anomaly detection,peak-to-valley price,and demand-side management of smart grids.The energy management and control system improved the intelligence of students’ apartment.It can manage students’ power consumption and collect students’ electricity data,which not only reduced the workload of the dormitory administrator and labor management cost,but also facilitated the analysis and study of students’ electricity consumption characteristics.This paper analyzed students’ electricity consumption from two aspects: electricity consumption characteristics and non-standard electricity consumption characteristics.And it is based on the data collected by energy management and control system in student apartments and data mining technology.The main work of this paper is as follows:(1)This paper collected data by using database technology and crawler technology,and cleaned data by using data processing technology so that the data meet the command of data analysis.(2)This paper studied and analyzed the characteristics of students’ electricity consumption and the relationship between students’ electricity consumption and temperature.Finally,this paper extracted students’ electricity characteristics curve.(3)This paper made a short-term electricity consumption forecasting by using regression model and ARIMA model,and compared the true value with forecasted value,which proves that the model has a good result of forecasting students’ electricity consumption.(4)This paper studied students’ non-standard electricity consumption characteristics.It introduced the principle of identification of non-standard electricity in the system and analyzed the non-standard electricity consumption in different time span and different temperature span.This paper provide students’ electricity characteristics,which provided a certain basis for the campus power management and fire management,and helped local smart grid to carry out different load forecasting based on different power consumers and provided data support power consumers’ identification and grid scheduling decisions.