High-Proportion Distributed Energy Grid-Connected Massive Monitoring Data Cloud Processing and Intelligent Decision-Making Technology

Abstract

In the daily operation of a high proportion of distributed energy grid related power equipment, many internal and external complex factors will cause a huge impact on power equipment, and this impact will significantly reduce the safety of power equipment. In order to solve the shortcomings of the existing research on large-scale monitoring data of high proportion distributed energy connected to the grid, this paper discusses the characteristics of cloud processing Flume, intelligent decision support technology, the functional requirements of large-scale monitoring data of high proportion distributed energy connected to the grid and the functional equation of monitoring data evaluation index. The project overview and monitoring data of cloud processing and intelligent decision technology application are briefly introduced. In addition, the workflow design of the system structure model of cloud processing and intelligent decision-making technology for large-scale monitoring data connected to the grid of high proportion of distributed energy is discussed. Finally, the application of cloud processing and intelligent decision-making technology in monitoring data is compared and analyzed. The experimental data show that, the accuracy rate of intelligent decision technology for the evaluation of power load absorption capacity, carrying capacity and generation capacity in the mass monitoring data of high proportion of distributed energy grid connection is between 95.2% and 98.7%. The cloud processing technology has a fast processing speed and high accuracy for monitoring data, so it is verified that the cloud processing and intelligent decision-making technology of massive monitoring data with high proportion of distributed energy connected to the grid has high application value.