Multi-Objective Optimization of a Family House Performance and Forecast of its Energy Needs by 2100

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    This paper describes a general multi-objective optimization approach of the energy performance of buildings using genetic algorithms, and the forecast of future energy needs according to the IPCC climate change scenarios. To this end, the energy performance of a family house is optimized and the optimal solution is studied in a future context marked by global warming and rise of temperatures.

     

     


     

  • Keywords


    Building simulation; Climate change; Genetic algorithms; Optimization; MOBO

  • References


      [1] Germanwatch / Climate Action Network International / New Climate Institute “Climate Change Performance Index 2018”

      [2] Règlement thermique de construction au Maroc (RTCM) – Agence Nationale pour le développement des Energies Renouvelables et de l’efficacité énergétique (ADEREE)

      [3] Intergovernmental Panel on Climate Change – Meteofrance – available online: http://www.meteofrance.fr/climat-passe-et-futur/le-giec-groupe-dexperts-intergouvernemental-sur-levolution-du-climat/les-scenarios-du-giec

      [4] G. Florides and S. Kalogirou, “Ground Heat Exchangers—A Review of Systems, Models and Applications,” Renewable Energy, Vol. 32, No. 15, 2007, 2461-2478. doi:10.1016/j.renene.2006.12.014

      [5] Matti Palonen, Mohamed Hamdy, Ala Hasan - MOBO a new software for multi-objective building performance optimization - Technical Research Centre of Finland, Espoo, Finland – 2013

      [6] Deb, K. Multi-Objective Optimization using evolutionary algorithms; John Wiley & Sons: Chichester, UK, 2001

      [7] Tuhus-Dubrow D, Krarti M. Genetic-algorithm based approach to optimize building envelope design for residential buildings. Build Environ 2010; 45:1574–81


 

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Article ID: 23235
 
DOI: 10.14419/ijet.v7i4.32.23235




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