Abstract
The present work warns of the potential performance of the mapreduce technique for handling big data from the intelligent measurement of electrical energy, this information is managed by the measurement data management system and is used to find the energy consumption pattern of the users. The large amount of information from the intelligent measurement of electrical energy requires a short-term analysis for a subsequent decision-making required to obtain the answer to the demand of the energy in each electric distribution company. In this way, this work presents a technique to handle a large amount of information in a short time to generate trends and statistics of electric energy consumption information from the information coming from several years of information storage.
| Translated title of the contribution | Electrical consumption pattern base on meter data management system using big data techniques |
|---|---|
| Original language | Spanish |
| Title of host publication | Proceedings - 2017 International Conference on Information Systems and Computer Science, INCISCOS 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 334-339 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781538626443 |
| DOIs | |
| State | Published - 29 Mar 2018 |
| Externally published | Yes |
| Event | 2nd International Conference on Information Systems and Computer Science, INCISCOS 2017 - Quito, Ecuador Duration: 23 Nov 2017 → 25 Nov 2017 |
Publication series
| Name | Proceedings - 2017 International Conference on Information Systems and Computer Science, INCISCOS 2017 |
|---|---|
| Volume | 2017-November |
Conference
| Conference | 2nd International Conference on Information Systems and Computer Science, INCISCOS 2017 |
|---|---|
| Country/Territory | Ecuador |
| City | Quito |
| Period | 23/11/17 → 25/11/17 |
Bibliographical note
Funding Information:III. FORMULACIÓN DEL PROBLEMA El problema de gestión de big data en SGDM requiere de un proceso recursivo en paralelo que permite adquirir el total o parte de la información según sean los requerimientos para el análisis o reportes usados para una posterior toma de decisión de la respuesta de la demanda eléctrica; por lo tanto, el análisis de big data proveniente de medición inteligente de energía eléctrica no es un problema trivial, requiere una gestión de la información que responda de manera oportuna y escalable y que permita realizar una asignación de recursos con el menor costo, considerando las restricciones de capacidad de cada SGDM, a través de un adecuado un gestor de reportes que nos permita obtener las tendencias del comportamiento del consumo eléctrico.
Publisher Copyright:
© 2017 IEEE.
