Machine learning-based energy management system for prosumer

Gde Dharma Nugraha, Budi Sudiarto, Kalamullah Ramli

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)


The rapid development of RES technology produces cheaper and compact devices. This condition has attracted the household to install the RES devices on their premises. Hence, the household has changed from the passive electricity consumer into the active prosumer. The active prosumer not only consumes the electricity but also have the capability to produce electricity. However, the electricity produced by RES devices is intermittence and unstable. Moreover, the behavior of the inhabitants of the prosumer also changes over time. Hence, a smart energy management system is needed by the prosumer to maintain the balance of its electricity demand and supply. In this paper, we explore the integration of the Machine-learning based on the prosumer’s EMS to address the uncertainty problem in the prosumer.

Original languageEnglish
Pages (from-to)309-313
Number of pages5
Issue number2
Publication statusPublished - Jun 2020


  • Energy Management System
  • HEMS
  • Local Market
  • Machine Learning
  • Prosumer


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