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Multi-Agent Recommendation System for Electrical Energy Optimization and Cost Saving in Smart Homes

Author

Listed:
  • Diego M. Jiménez-Bravo

    (Expert Systems and Applications Lab, Faculty of Science, University of Salamanca, Plaza de los Caídos s/n, 37002 Salamanca, Spain)

  • Javier Pérez-Marcos

    (Expert Systems and Applications Lab, Faculty of Science, University of Salamanca, Plaza de los Caídos s/n, 37002 Salamanca, Spain)

  • Daniel H. De la Iglesia

    (Expert Systems and Applications Lab, Faculty of Science, University of Salamanca, Plaza de los Caídos s/n, 37002 Salamanca, Spain)

  • Gabriel Villarrubia González

    (Expert Systems and Applications Lab, Faculty of Science, University of Salamanca, Plaza de los Caídos s/n, 37002 Salamanca, Spain)

  • Juan F. De Paz

    (Expert Systems and Applications Lab, Faculty of Science, University of Salamanca, Plaza de los Caídos s/n, 37002 Salamanca, Spain)

Abstract

The European Union Establishes that for the next few years, a cleaner and more efficient energy system should be used. In order to achieve this, this work proposes an energy optimization method that facilitates the achievement of these objectives. Existing technologies allow us to create a system that optimizes the use of energy in homes and offers some type of benefit to its residents. Specifically, this study has developed a recommendation system based on a multiagent system that allows to obtain consumption data from electronic devices in a home, obtain information on electricity prices from the Internet, and provide recommendations based on consumption patterns of users and electricity prices. In this way, the system recommends new hours in which to use the appliances, offering the economic benefit that it would propose recommendations for the user. In this way, it is possible to distribute and optimize the use of energy in homes and reduce the peaks in electricity consumption. The system provides encouraging results in order to resolve the problem proposed by the European Union by optimizing the use of energy among different hours of the day and saving money for the customer.

Suggested Citation

  • Diego M. Jiménez-Bravo & Javier Pérez-Marcos & Daniel H. De la Iglesia & Gabriel Villarrubia González & Juan F. De Paz, 2019. "Multi-Agent Recommendation System for Electrical Energy Optimization and Cost Saving in Smart Homes," Energies, MDPI, vol. 12(7), pages 1-22, April.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1317-:d:220432
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    Cited by:

    1. Yongxiu He & Meiyan Wang & Jinxiong Yu & Qing He & Huijun Sun & Fengyu Su, 2020. "Research on the Hybrid Recommendation Method of Retail Electricity Price Package Based on Power User Characteristics and Multi-Attribute Utility in China," Energies, MDPI, vol. 13(11), pages 1-18, May.

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