Reliable Reception And Fast Processing Of Streaming Big Data For Grid Monitoring Under The Cloud Platform

With the development of smart grids,the status monitoring of power equipment is gradually popularized and the explosive increase in the amount of streaming data for grid monitoring has also led to more arduous tasks for the power equipment monitoring center.As a data platform most likely to develop into smart grid equipment monitoring,cloud platforms have the advantages of storing and processing a large amount of streaming data,which can meet the needs of smart grids for big data storage and analysis.This paper studies the problems of unreliable reception and slow processing speed caused by the rapid in crease in the amount of streaming data in the power grid,and the difficulty of interoperability of models under different platforms.In order to improve the efficiency of streaming data processing,the discharge data parameter analysis is combined with the cloud platform,and the dual threshold filtering parameter extraction algorithm under the cloud platform is designed and used.After submitting the algorithm to the cluster,the efficiency of parameter extraction and pattern recognition is improved,and the data processing speed is accelerated.On this basis,it also studied the application of p redictive model markup language and Alluxio under the cloud platform,which reduced the huge workload of directly transferring models between different platforms,realized the intercommunication of models under Storm and Spark,and made use of Spark and Storm.The advantage of collaborative work realizes the cross-platform sharing of different systems or language models under the cloud platform,solves the problem of difficulty in intercommunication of models under different platforms,and improves the speed of data processing.The distributed scheduling system structure of the cloud platform is improved by increasing the communication between the scheduling hosts.A t the same time,an event insertion algorithm based on the priority number event queue is designed and used.The improved cloud platform distributed scheduling system and the event insertion algorithm based on the priority number event queue are used to ac hieve reliable data reception.