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Energies 2017, 10(11), 1925; https://doi.org/10.3390/en10111925

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

1
Faculty of Science and Technology, Free University of Bozen-Bolzano, piazza Università 5, 39100 Bolzano, Italy
2
Department of Civil, Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, 38123 Trento, Italy
3
Department of Design and Planning in Complex Environments, University Iuav of Venice, Dorsoduro 2206, 30123 Venezia, Italy
*
Author to whom correspondence should be addressed.
Received: 15 October 2017 / Revised: 30 October 2017 / Accepted: 16 November 2017 / Published: 21 November 2017
(This article belongs to the Section Energy Storage and Application)
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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. View Full-Text
Keywords: EN ISO 15927-4 reference year; typical meteorological year; genetic algorithm; building energy simulation; multi-objective optimization; Finkelstein-Schafer statistics EN ISO 15927-4 reference year; typical meteorological year; genetic algorithm; building energy simulation; multi-objective optimization; Finkelstein-Schafer statistics
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Pernigotto, G.; Prada, A.; Cappelletti, F.; Gasparella, A. Impact of Reference Years on the Outcome of Multi-Objective Optimization for Building Energy Refurbishment. Energies 2017, 10, 1925.

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