The Storage And Inquiry Of The Condition Monitoring Data Of The Electrical Equipment Based On Cloud Computing

As a representative of the future power grid, Smart Grid has been hot spots of research and application from its birth. In the environment of the smart grid, the condition monitoring data of the electrical equipment will surge and be far beyond the scope of the traditional grid. The. methods that conventional data storage and data processing will encounter great difficulties. As an emerging computing model, with features that large scale, high scalability and high reliability, Cloud Computing provides a new way of thinking to solve the above problem.In this paper, research and application status of the condition monitoring of the electrical equipment and cloud computing was first conducted in detail. By analyzing the specific applications of the condition monitoring of the existing grid power equipment, it defined the relevant issues which is sharing, integration and use of the condition monitoring data,high demand of real-time and reliability, difficult storage and processing of the on-line monitoring data that need to be solved. We targeted reliable storage and fast data processing for cloud computing which would be applied to condition monitoring of electrical equipment.Targeted for the requirements of high quality of service of condition monitoring of smart grid electrical equipment, this paper in-depth studied from sharing, real-time, reliability, etc respectively. To introduce a data processing architecture based on Hadoop, It studied the Hadoop distributed cluster technology and also business requirements and actual soft/hard power of the States Grid. This paper introduced both from the data structure design, program flow organization and programming, and several other aspects of the use of technology to introduce the realization of this model to solve the issues which is reliable storage and efficient processing of the mass condition monitoring data.Experiment to the proposed methods in paper. Simulation results show that methods are correct and efficiency. The new method is an effective solution to the problem of fast processing of condition monitoring data while achieving features of high reliability storage to meet the requirements of real-time and reliability of the on-line monitoring. This project provided a new idea for the issues of reliable storage and fast processing of the condition monitoring data of the electrical equipment provides a new way for the condition monitoring of the smart grid and lay the foundation for the smooth development of smart grid automation.