The Determination of Load Profiles and Power Consumptions of Home Appliances

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ENERGIES, vol.11, no.3, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 11 Issue: 3
  • Publication Date: 2018
  • Doi Number: 10.3390/en11030607
  • Journal Name: ENERGIES
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Keywords: home appliances, load profile, power consumption, demand management, ENERGY MANAGEMENT-SYSTEMS, DEMAND RESPONSE, ELECTRICITY CONSUMPTION
  • Gazi University Affiliated: Yes


In recent years, the increment of distributed electricity generation based on renewable energy sources and improvement of communication technologies have caused the development of next-generation power grids known as smart grids. The structures of smart grids have bidirectional communication capability and enable the connection of energy generated from distributed sources to any point on the grid. They also support consumers in energy efficiency by creating opportunities for management of power consumption. The information on power consumption and load profiles of home appliances is essential to perform load management in the dwelling accurately. In this study, the power consumption data for all the basic home appliances, utilized in a two-person family in cankiri, Turkey, was obtained with high resolution in one-second intervals. The detailed power consumption analysis and load profile were executed for each home appliance. The obtained data is not only the average power consumption of each appliance but also characterizes different operating modes or their cycles. In addition, the impact of these devices on home energy management studies and their standby power consumptions were also discussed. The acquired data is an important source to determine the load profile of individual home appliances precisely in home energy management studies. Although the results of this study do not completely reflect the energy consumption behavior of the people who live in this region, they can reveal the trends in load demands based on a real sample and customer consumption behavior of a typical two-person family.