Data mining and analysis for predicting electrical energy consumption

Abstract

In this study paper, the feasibility of constructing a complete smart system for anticipating electrical power consumption is created, as electricity's market share is expected to expand over the future decades. Smart grids and smart meters will help utility companies and their customers soon. New services and businesses in energy management need software development and data analytics skills. New services and enterprises are competitive. The project's electricity consumers are categorized by their hourly power usage percentage. This classification was done using data mining (five algorithms in specific) and data analysis theory. This division aims to help each group minimize energy use and expenditures, encourage energy-saving activities, and promote consumer involvement by giving tailored guidance. The intended segmentation is done through an iterative process using a computer classification computation, post-analysis, and data mining with visualization and statistical methodologies.

Development of Surface Mining 4.0 in Terms of Technological Shock in Energy Transition: A Review

“…Digital twins, by processing and visualizing large amounts of data about real physical processes asynchronously and The integration of various equipment complexes based on the Internet of Things requires the processing of incomparably larger amounts of information than that generated by individual devices, which is intended to be facilitated by the use of the Distributed Frequent Itemset Mining Algorithm [40]. It makes it possible to fill in the missing data in the flow of digital information coming from smart sensors without failures in the operation of its analysis systems based on the reliable extraction of key data from the general array (Data Mining [41]). An example of the use of such technologies in Surface Mining 4.0 is Apache Spark, which successfully uses the SWEclat algorithm to accelerate and parallel data scaling and the balanced loading of information analysis systems [42].…”

Wireless Digital Smart Energy Meter Based on GSM/SMS Technology

“…there it is established that an investigation of these deviations to develop the invoices and that it is the obligation of the companies adopt efficient mechanisms that make it possible to submit your invoicing to investigation of deviations significant, between the registered consumption of subscriber or user during a billing period and their previous consumption averages. (1,2,3) Now, configured a significant deviation, utility companies are forced to visit users' homes in order to determine the cause that originated them. This power to visit real estate is framed by the Energy Regulatory Commission and Gas, ERCG, which orders: Control over the operation of the meters.…”