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: 
a.bellazzi@itc.cnr.it
Page: 
158-164
|
DOI: 
https://doi.org/10.18280/ama_a.050309
Received: 
6 April 2018
|
Accepted: 
12 June 2018
|
Published: 
30 September 2018
| Citation

OPEN ACCESS

Abstract: 

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.

Keywords: 

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

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