电力能源实时数据仓库系统研究与实现-计算机软件与理论专业论文.docxVIP

Subject : Research and Implementation of Real-time Data Warehouse System for Electrical Energy Specialty : Computer Software and Theory Name : Yang Qi (Signature) Instructor : Xue Hongye (Signature) ABSTRACT Based on one Wenzhou leather company’s energy measuring data real-time monitoring system, this thesis analyzes company decision-supported data warehouse logical model and physical model according to the demand of company executives, and does the specific application research in the data extraction,transformation, loading and cleaning techniques,etc. Combined with data mining algorithm, this paper makes application research on power energy load prediction strategically and tactically. Finally, real-time data warehouse system and ETL tools based on this research have been designed and implemented. The main contents of this thesis are as follows: First of all, the demand on electric power real-time data warehouse system has been analyzed, and the system structure of electric power real-time data warehouse has been designed. According to business requirement, the two subject structures have been established: power consumption and industry energy consumption. Besides, logical model and physical model structures have been designed for these two subjects. Secondly, two methods on power energy load prediction are designed: strategic prediction and tactical prediction. Strategic prediction is mainly used on medium and long term power load for company executives while tactical prediction is used on short term power load for managers in production line. There are two algorithms in strategic prediction: KNN algorithm and DWKNN algorithm. The experimental data shows that performance of DWKNN algorithm is much better than KNN algorithm. While tactical prediction mainly predicts power load by the secondary exponential smoothing method. Since this method has little discrepancy, it reaches practical application standards. Thirdly, based on above study, the power energy real