Reconstruction of the Electric Consumption Pattern from Big Data using MapReduce Technique


  • Esteban Inga Ortega Universidad Politécnica Salesiana
  • Juan Inga Universidad Politécnica Salesiana
  • Estuardo Correa Universidad Politécnica Salesiana
  • Roberto Hincapié Universidad Pontificia Bolivariana



big data, map reduce, intelligent electrical network


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.



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Author Biographies

Esteban Inga Ortega, Universidad Politécnica Salesiana

Universidad Politécnica Salesiana

Coordinador Grupo de Investigación en Redes Eléctricas Inteligentes

Director de Carrera de Electricidad

Juan Inga, Universidad Politécnica Salesiana

Universidad Politécnica Salesiana

Grupo de Investigación en Telecomunicaciones

Carrera de Telecomunicaciones

Roberto Hincapié, Universidad Pontificia Bolivariana

Decano de Ingenierías


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How to Cite

Inga Ortega, E., Inga, J., Correa, E., & Hincapié, R. (2018). Reconstruction of the Electric Consumption Pattern from Big Data using MapReduce Technique. Enfoque UTE, 9(1), pp. 177 - 187.



Automation and Control, Mechatronics, Electromechanics, Automotive