A global survey of adverse energetic effects of increased wall insulation in office buildings: degree day and climate zone indicators

The energy efficiency of a building depends to a large measure on the characteristics of its envelope insulation. In the special case of internal gain dominated buildings, excessive building insulation may prevent the heat loss through the walls (anti-insulation effect), and thus generate the need for energy-intensive active systems to remove this thermal load. Detailed energetic simulations of a typical office building in Malaga (Spain), Dubai (UAE), and El Dorado (USA) show this anti-insulation effect and its dependency on climatic, constructive, and use factors. Results indicate that buildings in a predominantly cooling environment but within a certain range of heating degree days (HDD) will display this behavior: with very few to no HDD, the building’s energy consumption becomes insensitive to insulation increase (Dubai case); with a low number of HDDs the building becomes sensitive to anti-insulation (Malaga), and once a threshold is passed (El Dorado), the building’s energy consumption decreases with increased insulation. In order to further explore these limitations, simulations in 132 global locations of the building response to a step change in insulation are carried out. Results indicate that buildings in the Köppen climate zones Csa and Csb (Mediterranean climate), in locations with less than 2000 HDD and between 2000 and 5000 cooling degree days (CDD) are most susceptible to this anti-insulation behavior; however, quantitatively, the efficiency loss in these areas due to the insulation increase does not exceed 1 % of the overall energy consumption for the particular building studied and thus remains of limited importance.

[1]  Wilhelm A. Friess,et al.  Wall insulation measures for residential villas in Dubai: A case study in energy efficiency , 2012 .

[2]  Liwei Tian,et al.  Evaluation on energy and thermal performance for office building envelope in different climate zones of China , 2015 .

[3]  Patxi Hernandez,et al.  Energy demands and potential savings in European office buildings: Case studies based on EnergyPlus simulations , 2013 .

[4]  Mohammad S. Al-Homoud,et al.  Performance characteristics and practical applications of common building thermal insulation materials , 2005 .

[5]  Nelson Fumo,et al.  Methodology to estimate building energy consumption using EnergyPlus Benchmark Models , 2010 .

[6]  Daniel E. Fisher,et al.  EnergyPlus: creating a new-generation building energy simulation program , 2001 .

[7]  Zhenjun Ma,et al.  Building energy research in Hong Kong: A review , 2009 .

[8]  Fariborz Haghighat,et al.  Multiobjective optimization of building design using TRNSYS simulations, genetic algorithm, and Artificial Neural Network , 2010 .

[9]  Figen Balo,et al.  Application of three different methods for determination of optimum insulation thickness in external walls , 2011 .

[10]  Kambiz Rakhshan,et al.  Evaluating the sustainability impact of improved building insulation: A case study in the Dubai residential built environment , 2013 .

[11]  Paul Torcellini,et al.  Energy Use Intensity and its Influence on the Integrated Daylighting Design of a Large Net Zero Energy Building , 2011 .

[12]  Amir H. Ghoreishi,et al.  Parametric study of thermal mass property of concrete buildings in US climate zones , 2013 .

[13]  Afshin Afshari,et al.  Life-Cycle Analysis of Building Retrofits at the Urban Scale—A Case Study in United Arab Emirates , 2014 .

[14]  Keith J. Moss.  Energy Management in Buildings , 2005 .

[15]  Luis Pérez-Lombard,et al.  A review on buildings energy consumption information , 2008 .

[16]  Ralph Evins,et al.  A review of computational optimisation methods applied to sustainable building design , 2013 .

[17]  H. Radhi,et al.  Can envelope codes reduce electricity and CO2 emissions in different types of buildings in the hot climate of Bahrain , 2009 .

[18]  Michael J. Witte,et al.  Analytical and comparative testing of EnergyPlus using IEA HVAC BESTEST E100-E200 test suite , 2004 .

[19]  Hassan Radhi,et al.  Evaluating the potential impact of global warming on the UAE residential buildings – A contribution to reduce the CO2 emissions , 2009 .

[20]  Kostas Laskos,et al.  On the Establishment of Climatic Zones in Europe with Regard to the Energy Performance of Buildings , 2011 .

[21]  Meral Ozel,et al.  Thermal performance and optimum insulation thickness of building walls with different structure materials , 2011 .

[22]  Dongmei Pan,et al.  The effects of external wall insulation thickness on annual cooling and heating energy uses under different climates , 2012 .

[23]  Niccolò Aste,et al.  The influence of the external walls thermal inertia on the energy performance of well insulated buildings , 2009 .

[24]  Teuku Meurah Indra Mahlia,et al.  Cost benefits analysis and emission reductions of optimum thickness and air gaps for selected insulation materials for building walls in Maldives , 2010 .

[25]  Juan J. Sendra,et al.  Towards Energy Demand Reduction in Social Housing Buildings: Envelope System Optimization Strategies , 2012 .

[26]  Jon Hand,et al.  CONTRASTING THE CAPABILITIES OF BUILDING ENERGY PERFORMANCE SIMULATION PROGRAMS , 2008 .

[27]  P. Torcellini,et al.  Source Energy and Emission Factors for Energy Use in Buildings (Revised) , 2007 .

[28]  O. Kaynakli.  Parametric Investigation of Optimum Thermal Insulation Thickness for External Walls , 2011 .

[29]  L. J. Grobler,et al.  A new and innovative look at anti-insulation behaviour in building energy consumption , 2008 .

[30]  Philippe Rigo,et al.  A review on simulation-based optimization methods applied to building performance analysis , 2014 .

[31]  Evangelos Grigoroudis,et al.  A multi-objective decision model for the improvement of energy efficiency in buildings , 2010 .

[32]  Standard Ashrae.  Thermal Environmental Conditions for Human Occupancy , 1992 .