Open Access
Issue |
Sust. Build.
Volume 4, 2019
Zero Energy Mass Custom Homes
|
|
---|---|---|
Article Number | 5 | |
Number of page(s) | 14 | |
DOI | https://doi.org/10.1051/sbuild/2019006 | |
Published online | 11 December 2019 |
- EU, Directive 2010/31/EU of the European Parliament and of the Council of 19 May 2010 on the energy performance of buildings (recast), Off. J. Eur. Union 13–35 (2010) [Google Scholar]
- M. Ferrara, V. Monetti, E. Fabrizio et al., Cost-optimal analysis for nearly zero energy buildings design and optimization: a critical review, Energies 11, 1–32 (2018) [CrossRef] [Google Scholar]
- E. Pikas, M. Thalfeldt, J. Kurnitski, Cost optimal and nearly zero energy building solutions for office buildings, Energy Build. (2014) [Google Scholar]
- J. Kurnitski, A. Saari, T. Kalamees, M. Vuolle, J. Niemelä, T. Tark, Cost optimal and nearly zero (nZEB) energy performance calculations for residential buildings with REHVA definition for nZEB national implementation, Energy Build. 43 , 3279–3288 (2011) [CrossRef] [Google Scholar]
- D. D’Agostino, D. Parker, A framework for the cost-optimal design of nearly zero energy buildings (NZEBs) in representative climates across Europe, Energy (2018) [Google Scholar]
- BPIE, Nearly Zero Energy Buildings in Europe, 2016 [Google Scholar]
- S.P. Corgnati, E. Fabrizio, M. Filippi, V. Monetti, ‘Reference buildings for cost optimal analysis: Method of definition and application, Appl. Energy (2013) [Google Scholar]
- F. Garde et al., Design of net zero energy buildings: Feedback from international projects, Energy Proc. 61, 995–998 (2014) [CrossRef] [Google Scholar]
- BPIE, Cost Optimality: Discussing methodology and challenges within the recast Energy Performance of Buildings Directive, 2010 [Google Scholar]
- BSI ISO 15686-5, BS ISO 15686-5:2008-Buildings & constructed assets − Service life planning − Part 5: Life cycle costing, Int. Stand. (2008) [Google Scholar]
- A.T. Nguyen, S. Reiter, P. Rigo, A review on simulation-based optimization methods applied to building performance analysis, Appl. Energy (2014) [Google Scholar]
- S. Attia, M. Hamdy, W. O’Brien, S. Carlucci, Assessing gaps and needs for integrating building performance optimization tools in net zero energy buildings design, Energy Build. 60 , 110–124 (2013) [CrossRef] [Google Scholar]
- V. Machairas, A. Tsangrassoulis, K. Axarli, Algorithms for optimization of building design: a review, Renew. Sustain. Energy Rev. (2014) [Google Scholar]
- US Department of Energy and others, A common definition for zero energy buildings, Change 5 , 22 (2014) [Google Scholar]
- E.M. Malatji, J. Zhang, X. Xia, A multiple objective optimisation model for building energy efficiency investment decision, Energy Build. (2013) [Google Scholar]
- M. Hamdy, G.M. Mauro, Multi-objective optimization of building energy design to reconcile collective and private perspectives: CO2-eq vs. Discounted payback time, Energies (2017) [Google Scholar]
- H. Iba, C.C. Aranha, Introduction to genetic algorithms, Adaptation, Learning, and Optimization (2012) [CrossRef] [Google Scholar]
- M. Fesanghary, S. Asadi, Z.W. Geem, Design of low-emission and energy-efficient residential buildings using a multi-objective optimization algorithm, Build. Environ. (2012) [Google Scholar]
- D. Tuhus-Dubrow, M. Krarti, Genetic-algorithm based approach to optimize building envelope design for residential buildings, Build. Environ. (2010) [Google Scholar]
- J.A. Wright, H.A. Loosemore, R. Farmani, Optimization of building thermal design and control by multi-criterion genetic algorithm, Energy Build. (2002) [Google Scholar]
- K.J. Lomas, H. Eppel, Sensitivity analysis techniques for building thermal simulation programs, Energy Build. (1992) [Google Scholar]
- J.C. Lam, S.C.M. Hui, Sensitivity analysis of energy performance of office buildings, Build. Environ. (1996) [Google Scholar]
- P. Heiselberg, H. Brohus, A. Hesselholt, H. Rasmussen, E. Seinre, S. Thomas, Application of sensitivity analysis in design of sustainable buildings, Renew. Energy (2009) [Google Scholar]
- M.D. Morris, Factorial sampling plans for preliminary computational experiments, Technometrics (1991) [Google Scholar]
- M. Cervantes, The Monte Carlo Method, Math. Sci. Eng. (1972) [Google Scholar]
- University of Washington, Machine Learning: Clustering & Retrieval. [Online]. Available: https://www.coursera.org/lecture/ml-clustering-and-retrieval/complexity-of-brute-force-search-5R6q3. [Accessed: 10-Apr- 2019] [Google Scholar]
- G. Chiandussi, M. Codegone, S. Ferrero, F.E. Varesio, Comparison of multi-objective optimization methodologies for engineering applications, Comput. Math. Appl. (2012) [Google Scholar]
- T. Hatt et al., Kostenoptimierte Gebäude im Lebenszyklus, in Economicum Session 7 (2018) [Google Scholar]
- Passive House Institute, Passive House Planning Package (PHPP), passivehouse.com (2015) [Google Scholar]
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