Data Visualization Analysis Based On Power Internet Of Things

With the development of science and technology and the reform of the system,the power industry has undergone major changes.In recent years,the emergence of smart grid technologies and applications has attracted widespread attention in countries around the world,and sensors and measurement equipment in smart grids collect large-scale data.The Power Internet of Things forms the power of Internet of Things big data by recording the user’s electricity usage data and sending it to the cloud platform.Power Io T Big Data provides a new way to solve problems such as power load forecasting,anomaly detection and supply and demand balance.How to apply large-scale power Internet of Things data to promote and improve efficiency is an urgent problem in the smart grid.By using smart meters to collect user data,we can effectively reduce errors and minimize the amount of human intervention to process information.By using interactive real-time data visualization and time series modeling,this paper develops and constructs a power Io T data visualization analysis system to visually analyze the collected power big data,and can grasp the user’s electricity usage rules and predict the ARIMA model.Power consumption provides a strong support for users to save electricity,and also provides a basis for power companies to develop scheduling policies.The main work done in this paper is as follows:1)According to the actual power consumption big data,this paper develops a R-based power Io T data visualization analysis system for visual analysis of data collected by smart meters.It uses the plotly R package to visualize power data using the R/shiny web server architecture.2)Power Io T data visualization analysis system analyzes and predicts the user’s electricity consumption,and passes The ARIMA model built by the algorithm has the ability to automatically adjust,and can automatically generate the most suitable ARIMA model based on the data input by the user,and has a more accurate prediction of the user’s medium and long-term power consumption trend.3)Verification of the versatility of the system and the automatic adjustment ability of the algorithm,first in the public data set.It is proved that the visualization part of the system and the generated ARIMA model are suitable,and then the data of a domestic company is used to prove the automatic adjustment ability of the ARIMA model constructed by the algorithm.The force is very strong and can automatically generate the most suitable time series model.4)The power Io T data visualization analysis system completes the user’s hourly,day,days of the week,week,and month power usage comparisons,making the user’s power usage behavior clear and intuitive,and facilitating users to adjust their own power usage behavior to reduce electricity bills.The results show that the system has good visual analysis ability and strong versatility for power consumption big data.The analysis report made by the system can enable users to master their own power consumption behavior.Different time series can generate appropriate ARIMA models by using the constructed data.