Impact of Reference Years on the Outcome of Multi-Objective Optimization for Building Energy Refurbishment

Giovanni Pernigotto, Alessandro Prada, Francesca Cappelletti and Andrea Gasparella
Additional contact information
Giovanni Pernigotto: Faculty of Science and Technology, Free University of Bozen-Bolzano, piazza Università 5, 39100 Bolzano, Italy
Alessandro Prada: Department of Civil, Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, 38123 Trento, Italy
Francesca Cappelletti: Department of Design and Planning in Complex Environments, University Iuav of Venice, Dorsoduro 2206, 30123 Venezia, Italy
Andrea Gasparella: Faculty of Science and Technology, Free University of Bozen-Bolzano, piazza Università 5, 39100 Bolzano, Italy

Energies, 2017, vol. 10, issue 11, 1-23

Abstract: There are several methods in the literature for the definition of weather data for building energy simulation and the most popular ones, such as typical meteorological years and European test reference years, are based on Finkelstein–Schafer statistics. However, even starting from the same multi-year weather data series, the developed reference years can present different levels of representativeness, which can affect the simulation outcome. In this work, we investigated to which extent the uncertainty in the determination of typical weather conditions can affect the results of building energy refurbishment when cost-optimal approach is implemented for the selection of energy efficiency measures by means of the NSGA-II genetic algorithm coupled with TRNSYS simulations. Six different reference years were determined for two north Italy climates, Trento and Monza, respectively in the Alpine and in the continental temperate regions. Four types of energy efficiency measures, related to both building envelope and HVAC system, were applied to six existing building typologies. Results showed how the choice of reference year can alter the shape of the Pareto fronts, the number of solutions included and the selection among the alternatives of the energy efficiency measures, for the entire front and, in particular, for energy and economic optima.

Keywords: EN ISO 15927-4 reference year; typical meteorological year; genetic algorithm; building energy simulation; multi-objective optimization; Finkelstein-Schafer statistics (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 (6)

Downloads: (external link)
https://www.mdpi.com/1996-1073/10/11/1925/pdf (application/pdf)
https://www.mdpi.com/1996-1073/10/11/1925/ (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:11:p:1925-:d:119715

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 ().