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D2.1c Simulation Results of Reference Buildings

Authors: Bales, Chris; Gustafsson, Marcus; Chiara, Dipasquale; Roberto, Fedrizzi; Alessandro, Bellini; Matteo, D’Antoni; Fabian, Ochs; +2 Authors

D2.1c Simulation Results of Reference Buildings

Abstract

This report is the third part of the deliverable D2.1, where the other two parts report on the energy consumption in the building stock in Europe based on the available energy statistics (D2.1a) and the energy policies related to buildings (D2.1b).The aim of this report is to give complementary information about the heating and cooling demands of residential and office buildings based on simulations, so that the many gaps in the energy statistics can be filled and the statistics can be critically evaluated. The methodology results in a complete and consistent overview of the heating and cooling demands in residential and office buildings for seven different climate regions covering the whole of the EU and six different periods of construction, covering pre-1945 to post 2000. In addition, the data for the residential building stock is split into single family houses, small and large multifamily houses, while for offices the results are given for low and high rise offices with 6 or 12 office units per floor.The simulation models have been benchmarked (calibrated) against the energy statistics for each of the seven climate regions based on the aggregated data for the whole residential building stock and then for the office building stock in that climate region (in D2.1a). The methodology derives the aggregated average using weighted averages of data split into periods of construction and typology for both energy statistics and simulation results. The weighting is done based on heated and cooled floor area. As nearly all of the energy statistics are given in terms of consumption, while simulation results were calculated as demand, the demand data were converted to consumption data. One fixed conversion factor was used for heating (average efficiency 0.8) and one for cooling (average EER 2.5). Since the calculated demands strongly depend on the imposed heating or cooling set temperatures, this simulation parameter was varied so that the aggregated simulation result was the same as that for the consumption derived from the energy statistics. The calibrated models were then used to derive the average heating and cooling consumptions of the building stock in the seven climate regions.The methodology has a number of uncertainties, both in terms of the energy statistics as well as in terms of the simplifications and assumptions in the simulation models. During the calibration process a number of inconsistencies have been detected for individual countries and climate regions between simulation results and energy use from statistic data. The mismatches are analytically assessed, showing improvements necessary both in terms of statistic data necessary for reliable energy estimations and data to be gathered in order to guarantee consistent simulations outcomes.Beside the building stock survey completion and statistic data quality assessment, the work is also the basis for the definition of suitable Energy Renovation Packages and Products within the iNSPiRe project. The simulation results will be used to identify which building typologies, periods of construction and climate region have the largest potential for impact on the European scenario. Such information will be used within the iNSPiRe project to define reference Target buildings, as virtual demonstration cases to prove the potential improvements and impacts following the renovation process of a given share of the European building stock.

Country
Sweden
Related Organizations
Keywords

Energiteknik, Energy Engineering

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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Average