Code-to-Code Validation and Application of a Dynamic Simulation Tool for the Building Energy Performance Analysis

In this paper details about the results of a code-to-code validation procedure of an in-house developed building simulation model, called DETECt, are reported. The tool was developed for research purposes in order to carry out dynamic building energy performance and parametric analyses by taking into account new building envelope integrated technologies, novel construction materials and innovative energy saving strategies. The reliability and accuracy of DETECt was appropriately tested by means of the standard BESTEST validation procedure. In the paper, details of this validation process are accurately described. A good agreement between the obtained results and all the reference data of the BESTEST qualification cases is achieved. In particular, the obtained results vs. standard BESTEST output are always within the provided ranges of confidence. In addition, several test cases output obtained by DETECt (e.g., dynamic profiles of indoor air and building surfaces temperature and heat fluxes and spatial trends of temperature across walls) are provided.

[1]  Marija S. Todorovic,et al.  BPS, energy efficiency and renewable energy sources for buildings greening and zero energy cities planning: Harmony and ethics of sustainability , 2012 .

[2]  Julien Nembrini,et al.  Parametric scripting for early design performance simulation , 2014 .

[3]  Evangelos Grigoroudis,et al.  Towards a multi-objective optimization approach for improving energy efficiency in buildings , 2008 .

[4]  Matthias Haase,et al.  A numerical model to evaluate the thermal behaviour of PCM glazing system configurations , 2012 .

[5]  Per Heiselberg,et al.  Review of thermal energy storage technologies based on PCM application in buildings , 2013 .

[6]  Harry Boyer,et al.  Model optimization and validation with experimental data using the case study of a building equipped with photovoltaic panel on roof: Coupling of the building thermal simulation code ISOLAB with the generic optimization program GenOpt , 2013 .

[7]  A. Abdel-azim Fundamentals of Heat and Mass Transfer , 2011 .

[8]  Kevan A. C. Martin,et al.  Problems in the calculation of thermal bridges in dynamic conditions , 2011 .

[9]  Mohan Gupta Fundamentals of Heat and Mass Transfer , 2014 .

[10]  Abdullatif Ben-Nakhi,et al.  Development and integration of a user friendly validation module within whole building dynamic simulation , 2003 .

[11]  R. Judkoff,et al.  International Energy Agency building energy simulation test (BESTEST) and diagnostic method , 1995 .

[12]  Sandra Fillebrown,et al.  The MathWorks' MATLAB , 1996 .

[13]  P. T. Tsilingiris Parametric space distribution effects of wall heat capacity and thermal resistance on the dynamic thermal behavior of walls and structures , 2006 .

[14]  András Zöld,et al.  Definition of nearly zero-energy building requirements based on a large building sample , 2014 .

[15]  John Haymaker,et al.  Formalizing Approximations , Assumptions , and Simplifications to Document Limitations in Building Energy Performance Simulation , 2011 .

[16]  Shady Attia State of the Art of Existing Early DesignSimulation Tools for Net Zero EnergyBuildings : A Comparison of Ten Tools , 2011 .

[17]  Kristoffer Negendahl,et al.  Building performance simulation in the early design stage: An introduction to integrated dynamic models , 2015 .

[18]  David E. Bradley,et al.  Experiences with and interpretation of standard test methods of building energy analysis tools , 2004 .

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

[20]  Francesco Calise,et al.  Buildings dynamic simulation: Water loop heat pump systems analysis for European climates , 2012 .

[21]  Nathan Mendes,et al.  Capacitive effect on the heat transfer through building glazing systems , 2011 .

[22]  Ali Joudi,et al.  Energy efficient surfaces on building sandwich panelsA dynamic simulation model , 2011 .

[23]  Lars Eriksson,et al.  Whole-building simulation with symbolic DAE equations and general purpose solvers , 2004 .

[24]  Shengwei Wang,et al.  A simplified dynamic model for existing buildings using CTF and thermal network models , 2008 .

[25]  Mohammad S. Al-Homoud,et al.  Computer-aided building energy analysis techniques , 2001 .

[26]  Robert Weber,et al.  TRNSYS17: NEW FEATURES OF THE MULTIZONE BUILDING MODEL , 2009 .

[27]  Shady Attia,et al.  Simulation-based decision support tool for early stages of zero-energy building design , 2012 .

[28]  新 雅夫,et al.  ASHRAE(American Society of Heating,Refrigerating and Air-Conditioning Engineers)大会"国際年"行事に参加して , 1975 .

[29]  Adelqui Fissore,et al.  Thermal simulation of an attached sunspace and its experimental validation , 2007 .

[30]  Nuno M. Mateus,et al.  Validation of a lumped RC model for thermal simulation of a double skin natural and mechanical ventilated test cell , 2016 .

[31]  Pau Fonseca i Casas,et al.  Formal simulation model to optimize building sustainability , 2014, Adv. Eng. Softw..

[32]  Alfonso P. Ramallo-González,et al.  Lumped parameter models for building thermal modelling: An analytic approach to simplifying complex multi-layered constructions , 2013 .

[33]  Benjamin Paris,et al.  Heating control schemes for energy management in buildings , 2010 .

[34]  Paulo Santos,et al.  Review of passive PCM latent heat thermal energy storage systems towards buildings’ energy efficiency , 2013 .

[35]  Andreas K. Athienitis,et al.  Modeling of energy performance of a house with three configurations of building-integrated photovoltaic/thermal systems , 2010 .

[36]  Umberto Montanaro,et al.  Adaptive Control for Building Thermo-hygrometric Analysis: A Novel Dynamic Simulation Code for Indoor Spaces with Multi-enclosed Thermal Zones☆ , 2015 .

[37]  Francesco Calise,et al.  Solar heating and cooling systems by CPVT and ET solar collectors: A novel transient simulation model , 2013 .

[38]  Dirk Saelens,et al.  Comparison of steady-state and dynamic building energy simulation programs , 2004 .

[39]  Per Heiselberg,et al.  Comparative Test Case Specification – Test Cases DSF100_2 and DSF400_3: Report for IEA ECBCS Annex 43/SHC Task 34 Validation of Building Energy Simulation Tools , 2005 .

[40]  Umberto Montanaro,et al.  Dynamic building energy performance analysis: A new adaptive control strategy for stringent thermohygrometric indoor air requirements , 2016 .

[41]  Emily M. Ryan,et al.  Validation of building energy modeling tools under idealized and realistic conditions , 2012 .

[42]  P. Curtiss,et al.  Heating and Cooling of Buildings , 2009 .

[43]  Anna Laura Pisello,et al.  A Building Energy Efficiency Optimization Method by Evaluating the Effective Thermal Zones Occupancy , 2012 .

[44]  Umberto Montanaro,et al.  Innovative technologies for NZEBs: An energy and economic analysis tool and a case study of a non-residential building for the Mediterranean climate , 2016 .

[45]  D. Bouris,et al.  Calculation of the distribution of incoming solar radiation in enclosures , 2009 .

[46]  Edward Henry Mathews,et al.  A two-port envelope model for building heat transfer , 1998 .

[47]  K. A. Antonopoulos,et al.  On the dynamic thermal behaviour of indoor spaces , 2001 .

[48]  Christian Ghiaus,et al.  Calculation of optimal thermal load of intermittently heated buildings , 2010 .

[49]  Karolos-Nikolaos Kontoleon,et al.  Dynamic thermal circuit modelling with distribution of internal solar radiation on varying façade orientations , 2012 .

[50]  David E. Claridge,et al.  PI tuning and robustness analysis for air handler discharge air temperature control , 2012 .

[51]  Harry Boyer,et al.  A nodal thermal model for photovoltaic systems: Impact on building temperature fields and elements of validation for tropical and humid climatic conditions , 2009 .

[52]  Anna Laura Pisello,et al.  A method for assessing buildings’ energy efficiency by dynamic simulation and experimental activity , 2012 .

[53]  Per Heiselberg,et al.  Development and sensitivity study of a simplified and dynamic method for double glazing facade and verified by a full-scale façade element , 2014 .

[54]  P. T. Tsilingiris,et al.  Wall heat loss from intermittently conditioned spaces—The dynamic influence of structural and operational parameters , 2006 .

[55]  Adolfo Palombo,et al.  Building energy performance analysis by an in-house developed dynamic simulation code: An investigation for different case studies , 2014 .

[56]  Jin Wen,et al.  Review of building energy modeling for control and operation , 2014 .

[57]  Harry Boyer,et al.  A thermal model for phase change materials in a building roof for a tropical and humid climate: Model description and elements of validation , 2014 .

[58]  R. Judkoff,et al.  Applying the building energy simulation test (BESTEST) diagnostic method to verification of space conditioning equipment models used in whole-building energy simulation programs , 2002 .

[59]  Chris Bales,et al.  Combining thermal energy storage with buildings – a review , 2015 .

[60]  Nelson Fumo,et al.  A review on the basics of building energy estimation , 2014 .

[61]  H. H. Epps,et al.  Effect of geometric configuration and surface area on the thermal transmittance of edge-sealed draperies , 1986 .

[62]  Jay Burch,et al.  Methodology for Validating Building Energy Analysis Simulations , 2008 .

[63]  Hongxing Yang,et al.  Using phase change materials in photovoltaic systems for thermal regulation and electrical efficiency improvement: A review and outlook , 2015 .

[64]  Jan Hensen,et al.  Integrated building performance simulation: Progress, prospects and requirements , 2015 .