Multi-Objective Optimization of Building Energy Design to Reconcile Collective and Private Perspectives: CO 2 -eq vs. Discounted Payback Time

Mohamed Hamdy and Gerardo Maria Mauro
Additional contact information
Mohamed Hamdy: Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, Byggteknisk, 2-236, Gløshaugen, Høgskoleringen 7A, Trondheim 7491, Norway
Gerardo Maria Mauro: Department of Industrial Engineering, Università degli studi di Napoli Federico II, Piazzale Tecchio 80, Naples 80125, Italy

Energies, 2017, vol. 10, issue 7, 1-26

Abstract: Building energy design is a multi-objective optimization problem where collective and private perspectives conflict each other. For instance, whereas the collectivity pursues the minimization of environmental impact, the private pursues the maximization of financial viability. Solving such trade-off design problems usually involves a big computational cost for exploring a huge solution domain including a large number of design options. To reduce that computational cost, a bi-objective simulation-based optimization algorithm, developed in a previous study, is applied in the present investigation. The algorithm is implemented for minimizing the CO 2 -eq emissions and the discounted payback time (DPB) of a single-family house in cold climate, where 13,456 design solutions including building envelope and heating system options are explored and compared to a predefined reference case. The whole building life is considered by assuming a calculation period of 30 years. The results show that the type of heating system significantly affects energy performance; notably, the ground source heat pump leads to the highest reduction in CO 2 -eq emissions, around 1300 kgCO 2 -eq/m 2 , with 17 year DPB; the oil fire boiler can provide the lowest DPB, equal to 8.5 years, with 850 kgCO 2 -eq/m 2 reduction. In addition, it is shown that using too high levels of thermal insulation is not an effective solution as it causes unacceptable levels of summertime overheating. Finally a multi-objective decision making approach is proposed in order to enable the stakeholders to choice among the optimal solutions according to the weight given to each objective, and thus to each perspective.

Keywords: building performance simulation; energy design; heating systems; building envelope; multi-objective optimization; Pareto front; genetic algorithm; low-carbon buildings (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://www.mdpi.com/1996-1073/10/7/1016/pdf (application/pdf)
https://www.mdpi.com/1996-1073/10/7/1016/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:10:y:2017:i:7:p:1016-:d:105054

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().