Abstract
The work presents the performance of the MapReduce technique to reconstruct the load curve from a previously stored amount of information coming from smart metering of electrical energy and currently considered as Big Data. The management of information in the stage of an intelligent electrical network considered as a System of Management of Measured Data or MDMS needs reducing the times with respect to the reports that are required in a certain moment for decision making in relation to the electrical demand response. Therefore, this paper proposes the use of MapReduce as a technique to obtain information of the load curve in a suitable time to obtain trends and statistics related to the residential electric pattern.
| Translated title of the contribution | Reconstruction of the Electricity Consumption Pattern from Big Data Using the Mapreduce Technique |
|---|---|
| Original language | Spanish (Ecuador) |
| Pages (from-to) | 177-187 |
| Number of pages | 11 |
| Journal | Enfoque Ute |
| Volume | 9 |
| Issue number | 9 |
| DOIs | |
| State | Published - 30 Mar 2018 |
Keywords
- Big data
- Map reduce
- Meter data management system
- Smart gridsmart metering
CACES Knowledge Areas
- 317A Electricity and Energy
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Dive into the research topics of 'Reconstruction of the Electricity Consumption Pattern from Big Data Using the Mapreduce Technique'. Together they form a unique fingerprint.Projects
- 1 Finished
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Optimal Planning and Deployment of Overhead and Underground Electrical Distribution Networks
Inga Ortega, E. M. (PI), Campaña Molina, M. A. (Col), Santacruz Carcelen, E. G. (Student), Villacres Quishpe, F. J. (Student) & Herrera Cisneros, E. B. (Student)
22/01/18 → 30/12/18
Project: Research and Development
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