Supporting Decision Methodology for the Refurbishment of Buildings: Optimization in nZEB Perspective

Supporting Decision Methodology for the Refurbishment of Buildings: Optimization in nZEB Perspective

Alice BellazziBenedetta Barozzi Giulia Guazzi Italo Meroni 

Construction Institute of Technologies, National Research Council of Italy (ITC-CNR), via Lombardia 49, San Giuliano, Milanese 20098, Italy

Corresponding Author Email:
6 April 2018
12 June 2018
30 September 2018
| Citation



The improvement of the performance in building sector is recognized as one of the major action to meet the requirements for a sustainable future. Over the years much progress has been made for this aim. Nearly Zero Energy Building (nZEB) and Cost-Optimal approach are common concepts in design and refurbishment phase of buildings. In particular, the Cost-Optimal allows the definition of the best solutions by coupling energy and economic analyses. Nevertheless, between similar results from energy efficiency and costs point of view, other variables should be evaluated for retrofit interventions of buildings, considering for example such as environmental aspects. Several techniques are available for coupling all these aspects in an overall assessment perspective of building behavior. Among them, the Multi-Objective Optimization (MOO) is suitable for this purpose.

In the present paper, through thermo-dynamic simulations, MOO is applied to the cost-optimal solutions of a real residential building in a nZEB perspective in order to define the best refurbishment hypotheses, 

Crossing the Cost Optimal analyses with other meaningful variables: fixing two objectives, like the minimization of users discomfort and the incorporated CO2 in the refurbishment materials, up to 10 variables that can be analysed in the same simulation.


nearly zero energy building, cost-optimal, multi-objective optimization, retrofit

1. Introduction
2. Method
3. Case Study Optimization
4. Results
5. Conclusions

[1] Asadi E, Gameiro da Silva M, Antunes CH, Dias L. (2012). Multi-objective optimization for building retrofit strategies: a model and an application. Energy and Buildings 44: 81-87.

[2] European Commission. (2016). Proposal for the Directive of the European Parliament and of the Council amending Directive 2010/31/EU on the energy performance of buildings.

[3] Marsh G. (2002). Zero Energy buildings: key role for RE at UK housing development. Refocus 3(3): 58-61.

[4] Panagiotidou M, Fuller R.J. (2013). Progress in ZEBs - A review of definitions, policies and construction activity. Energy Policy 62: 196–206.

[5] Wang N, Phelan PE, Gonzalez J, Harris C, Henze GP, Hutchinson R, Langevin J, Lazarus MA, Nelson B, Pyke C, Roth K, Rouse D, Sawyer K, Selkowitz S. (2017). Ten questions concerning future buildings beyond zero energy and carbon neutrality. Building and Environment 119: 169–182.

[6] Almeida M, Ferreira M. (2017). Cost effective energy and carbon emissions optimization in building renovation (Annex 56). Energy and Building 152: 718-738.

[7] Almeida M, Ferreira M. (2015). IEA EBC Annex56 vision for cost effective energy and carbon emissions optimization in building renovation. Energy Procedia 78: 2409-2414.

[8] Lucchi E, Tabak M, Troi A. (2017). The Cost Optimality Approach for the internal insulation of historic buildings. Energy Procedia 133: 412-423.

[9] Guazzi G, Bellazzi A, Meroni I, Magrini A. (2017). Refurbishment design through cost-optimal methodology. The case study of a social housing in the northern Italy. International Journal of Heat and Technology 35(Sp.1): S336-S344.

[10] European Standard EN-15251. (2007). Indoor environmental input parameters for design and assessment of energy performance of buildings addressing indoor air quality, thermal environment, lighting and acoustics.

[11] European Standard EN-15459-1. (2017). Energy performance of buildings - Economic evaluation procedure for energy systems in buildings.

[12] Attia S, Gratia E, De Herde A, Hensen J. (2012). Simulation-based decision support tool for early stages of zero-energy building design. Energy and Buildings 49: 2-15.

[13] Di Giuseppe E, Massi A, D’Orazio M. (2017). Probabilistic life cycle cost analysis of building energy efficiency measures: selection and characterization of the stochastic inputs through a case study. Procedia Engineering 180: 491-501.

[14] Wu D, Tang L, Lia H, Ouyanga L. (2016). A co-evolutionary particle swarm optimization with dynamic topology for solving multi-objective optimization problems. AMSE JOURNALS-2016-Series: Advances A 53(1): 145-159. 

[15] Camporeale PE, del Pilar Mercader Moyanob M, Czajkowski JD. (2017). Multi-objective optimisation model: A housing block retrofit in Seville. Energy and Buildings 153: 476–484.

[16] Ascione F, Bianco N,  De Masi RF, Mauro GM, Vanoli GP. (2017). Resilience of robust cost-optimal energy retrofit of buildings to global warming: A multi-stage, multi-objective approach. Energy and Buildings 153: 150-167.

[17] Dalla Mora T, Peron F, Romagnoni P, Almeida M, Ferreira M. (2018). Tools and procedures to support decision making for cost-effective energy and carbon emissions optimization in building renovation. Energy and Buildings 167: 200–215.

[18] Morcka O, Almeidab M, Ferreirac M, Britod N, Thomsene K. E, Østergaardf I. (2015). Shining examples analysed within the EBC Annex 56 project. accessed on 14 March 2018

[19] D’Agostino D, Parker D. (2018). A framework for the cost-optimal design of nearly zero energy buildings (NZEBs) in representative climates across Europe. Energy 149: 814-829.

[20] Nguyen AT, Reiter S, Rigo P. (2014). A review on simulation-based optimization methods applied to building performance analysis. Applied Energy 113: 1043–1058.

[21] Belussi L, Danza L, Meroni I, Salamone F, Ragazzi F, Mililli M. (2013). Energy performance of buildings: A study of the differences between assessment methods 53-75. Energy Consumption: Impacts of Human Activity, Current and Future Challenges, Environmental and Socio-Economic Effects, Nova Science Publishers: New York, NY, USA.

[22] Danza L, Belussi L, Meroni I, Salamone F, Floreani F, Piccinini A, Dabusti A. (2016). A simplified thermal model to control the energy fluxes and to improve the performance of buildings. Energy Procedia 101.

[23] Commission Delegated Regulation (EU) No 244/2012. (2012). Supplementing Directive 2010/31/EU of the European Parliament and of the Council on the energy performance of buildings by establishing a comparative methodology framework for calculating cost-optimal levels of minimum energy performance. Official Journal of the European Union. http//

[24] EN ISO 13790. (2008). Energy performance of buildings - Calculation of energy use for space heating and cooling.

[25] European Standard EN-15459. (2007). Energy performance of buildings - Economic evaluation procedure for energy systems in buildings.

[26] Price list for execution of public works and maintenances of the city of Milan – 2018

[27] The Italian regulatory Authority for Electricity and gas and water., accessed on 14 March 2018.

[28] The World Bank., accessed on 14 March 2018.

[29] Worldwide inflation data., accessed on 14 March 2018.