Advertisement

Simulating the Optimization of Energy Consumption in Homes

  • Fernanda P. MotaEmail author
  • Plauto W. Filho
  • Jonas Casarin
  • Robledo Castro
  • Vagner Rosa
  • Silvia S. da C. Botelho
Conference paper
  • 898 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9086)

Abstract

According to Brazilian National Electric Energy Agency (ANEEL), the electric energy consumption is one of the main indicators of both the economic development and the quality of life of a society. However, the electric energy consumption data of individual home use is hard to obtain due to several reasons, such as privacy issues [1]. In this sense, the social simulation based on multiagent systems comes as a promising option to deal with this difficulty through the production of synthetic electric energy consumption data.

Keywords

Multiagent System Residential Sector Electric Energy Consumption Social Simulation Persuasive Technology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Aneel.: Energia no Brasil e no Mundo, Atlas de Energia Elétrica do Brasil (2002). Dis-ponível em www.aneel.gov.br (Acessado em Janeiro de 2014)
  2. 2.
    Russel, S., Norvig, P.: Artificial Intelligence: A modern approach, 2nd edition. Pearson Education (2003)Google Scholar
  3. 3.
    Dimuro, G.P., Costa, A.C.R., Palazzo, L.A.M.: Systems of exchange values as tools for multi-agent organizations. Journal of the Brazilian Computer Society 11(1), 3150 (2005)CrossRefGoogle Scholar
  4. 4.
    Wooldridge, M.: An introduction to multiagent systems. Whiley, Chichester (2002)Google Scholar
  5. 5.
    Swan, L.G., Ugursal, V.I.: Modeling of end-use energy consumption in the residential sector: A review of modeling techniques. Renewable and Sustainable Energy Reviews 13, 1819–1835 (2009)CrossRefGoogle Scholar
  6. 6.
    Hansen, A.M.D.: Padrões de Consumo de Energia Elétrica em Diferentes Tipologias de Edificações Residenciais em Porto Alegre. In: UFRGS, Porto Alegre (2000)Google Scholar
  7. 7.
    Picolo, L.S.G., Baranauskas, M.C.C.: Energy, environment, and conscious consumption: making connections through design. In: IHC Proceedings, Cuiabá, Brazil (2012)Google Scholar
  8. 8.
    Richardson, I., Thomson, M., Infield, D.: A high-resolution domestic building occupancy model for energy demand simulations. Energy and Buildings 40, 1560–1566 (2008)CrossRefGoogle Scholar
  9. 9.
    Widen, J., Wackelgard, E.: A high-resolution stochastic model of domestic activity patterns and electricity demand. Applied Energy 87, 1880–1892 (2010)CrossRefGoogle Scholar
  10. 10.
    Wood, G., Newborough, M.: Design and functionality of prospective energy-consumption displays. In: Proceedings of the 3rd International Conference on Energy Efficiency in Domestic Appliances and Lighting, pp. 757–70 (2003)Google Scholar
  11. 11.
    Kushiro, N., Suzuki, S., Nakata, M., Takahara, H., Inoue, M.: Integrated residential gateway controller for home energy management system. IEEE Transactions Consumer Electronics 49(3), 629–636 (2003)CrossRefGoogle Scholar
  12. 12.
    POF. Pesquisa de orc¸amentos familiares 2008–2009. despesas, rendimentos e condições de vida. Instituto Brasileiro de Geografia e F´ısica (Rio de Janeiro 2010)Google Scholar
  13. 13.
    Fogg, B. J.: Persuasive technology: using computers to change what we think and do. San Francisco, Calif. Oxford: Morgan Kaufmann; Elsevier Science (2003)Google Scholar
  14. 14.
    Cialdini, R.B.: Influence: The Psychology of Persuasion, revised edition. Harper-Collins (2007)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Fernanda P. Mota
    • 1
    Email author
  • Plauto W. Filho
    • 1
  • Jonas Casarin
    • 1
  • Robledo Castro
    • 1
  • Vagner Rosa
    • 1
  • Silvia S. da C. Botelho
    • 1
  1. 1.Centro de Ciências ComputacionaisUniversidade Federal Do Rio Grande- FurgRio GrandeBrazil

Personalised recommendations