Design And Implementation Of Online Business Intelligence System For Power Industry

With China's increasing international status,China is now entering the world stage center as never before,and energy governance has become an important way for China to actively participate in global governance.After China has made major commitments to jointly build a green and low-carbon global energy governance,increase the proportion of non-fossil energy consumption,and reduce carbon emissions,how to fully and rationally use electric energy has become the top priority of the work.The power industry contains a large amount of data resources.According to statistics,power big data mainly comes from power generation,transmission,substation,power distribution,power consumption and dispatching.It can be roughly divided into three categories:Power grid operation and equipment detection or monitoring data;Second,power enterprise marketing data,such as transaction price,electricity sales,electricity customers and other aspects of data;Third,power enterprise management data.Through the analysis of massive data,power companies can build power consumption models and parameters for different types of users.Therefore,it can provide reference for the power enterprise's strategy formulation,and effectively promote the balance between grid power generation and load.This project aims to design and implement an online business intelligence system for the power industry.Apply high-dimensional data display,automated page generation technology and data analysis and forecasting methods to form a set of process services from data cleansing to customized layout and then automatically generate pages.Compared with the previous business intelligence platform,the system has the ability to process complex data,interactive and highly automated interface,and more importantly,the system can automatically generate pages with one button,which is lighter than other business intelligence platforms.,Convenience.These characteristics are very friendly and practical for non-computer professionals.In order to realize the system,the relevant business intelligence platform on the market has been researched,the advantages and disadvantages of each platform are analyzed,and the functional characteristics and technical feasibility of the platform are clarified.Then analyze the key technical issues of the system.In order to reduce the entry threshold of the system and reduce the operational burden of the user,the system can support automated generation of website scripts,and the generated scripts can be run on various clients;in order to make the data prediction more accurate,the system firstly operates the original grid.The data is heavily preprocessed to remove some dirty data and useless data.Based on the three models of Lasso regression,Ridge regression and kernel-ridge regression,a large number of experiments are carried out to analyze the applicable scenarios of each model,and recommendations are made according to the degree of deviation of various models.