Energy Efficiency Analysis And Mining Research Based On User-Side Energy Data

With the power system reform in our country and the development of smart grid,energy-saving services have become the general trend of future development.The core of energy-saving is energy-efficiency management,and the energy efficiency analysis has become the core business of intelligent energy management and control.Massive energy consumption data mining,dirty data processing and energy data storage continue to bring new challenges to energy efficiency analysis.Traditional manual data collection and uploading can no longer meet the requirements of smart grid data processing.Therefore,it is of great practical significance to establish a user-side energy efficiency service system,which provide energy efficiency services to users and study the mining algorithm of massive energy consumption data.Based on the above problems,this paper mainly studies the following study :First in view of the problems such as high energy efficiency level,excessive energy efficiency indicators and unstable weight distribution of power users,the researches on index screening and weight distribution in energy efficiency analysis business are carried out.Based on the selection of the initial set of indicators for establishing energy efficiency evaluation system,the energy efficiency analysis model and the PCA and G1 method are put forward to carry out an example analysis of the optimization algorithm the model to the platform relying on the subject;Then according to the characteristics of large amount of data and complex data of energy consumption data at the user side,a data mining algorithm based on user-side energy data is researched.The data mining technology in energy efficiency management business is studied,which effectively combines with clustering based on dense points algorithm and the minimum and maximum K-means clustering algorithm.The energy efficiency analysis is studied deeply from the aspects of determining the number of clusters and improving the clustering accuracy,and a refinement of user-side energy-using data mining algorithm is proposed.Finally develops a cloud computing platform for energy efficiency assessment and service.The platform for sale and supply of refined energy services cloud platform,the platform collects data on energy use and evaluates the system based on the using situations and through technology and experts means to collect data so as to realize one-key assessment and tap the potential energy efficiency issues.Based on the energy efficiency assessment report,the platform provides resources and service support to meet users need and solve energy efficiency problems.