A comprehensive evaluation of a monthly-based energy auditing tool through dynamic simulations, and monitoring in a renovation case study

Abstract An energy auditing tool (PHPP) was evaluated against a dynamic simulation tool (TRNSYS) and used for the assessment of energy conservation measures in a demo case study. The comprehensive comparison of useful heating and cooling demands and loads included three building types (single-, multi-family house, and office), three building energy levels (before renovation and after renovation with a heating demand of 45 and 25 kWh/(m²·a)) and seven European climates. Dynamic simulation results proved PHPP (monthly energy balance) to be able to calculate heating demand and energy savings with good precision and cooling demand with acceptable precision compared to detailed numerical models (TRNSYS). The average deviation between the tools was 8% for heating and 15% for cooling (considering climates with a relevant cooling load only). The higher the thermal envelope quality was, i.e. in case of good energy standards and in cold climates, the better was the agreement. Furthermore, it was confirmed that PHPP slightly overestimates the heating and cooling loads by intention for system design. The renovation design of a real multi-family house was executed using PHPP as energy auditing tool. Several calculation stages were performed for (a) baseline, (b) design phase, and (c) verification with monitoring in order to calculate the corresponding heating demand. The PHPP model was calibrated twice, before and after the renovation. The necessity for tool calibration, especially for the baseline, was highlighted increasing the confidence with respect to a number of boundary conditions. In this study, PHPP was tested as an energy auditing tool aiming to be a versatile and less error-prone alternative to more complex simulation tools, which require much more expert knowledge and training.

[1]  Eric Hirst,et al.  Actual electricity savings and audit predictions for residential retrofit in the pacific northwest , 1985 .

[2]  Michael E. Webber,et al.  Using BEopt (EnergyPlus) with energy audits and surveys to predict actual residential energy usage , 2015 .

[3]  Peyman Moghadam,et al.  HeatWave : a handheld 3D thermography system for energy auditing , 2013 .

[4]  Andrea Gasparella,et al.  Extensive Comparative Analysis Of Two Building Energy Simulation Codes For Southern Europe Climates: Heating And Cooling Energy Needs and Peak Loads Calculation In TRNSYS And EnergyPlus , 2012 .

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

[6]  Ray Galvin,et al.  Introducing the prebound effect: the gap between performance and actual energy consumption , 2012 .

[7]  Stéphane Bertagnolio,et al.  Simulation of a building and its HVAC system with an equation solver: Application to audit , 2010 .

[8]  Gian Luca Morini,et al.  Energy Audit of an Industrial Site: A Case Study , 2014 .

[9]  Kimon A. Antonopoulos,et al.  Comparison of Heating and Cooling Loads of a Typical Building with TRNSYS and eQUEST , 2016 .

[10]  Sture Holmberg,et al.  Energy performance comparison of three innovative HVAC systems for renovation through dynamic simulation , 2014 .

[11]  Henk Visscher,et al.  Theoretical vs. actual energy consumption of labelled dwellings in the Netherlands: Discrepancies and policy implications , 2013 .

[12]  Borong Lin,et al.  Building simulation as assistance in the conceptual design , 2008 .

[13]  Xing Han,et al.  Energy audit and air-conditioning system renovation analysis on office buildings using air-source heat pump in Shanghai , 2014 .

[14]  Seong-Hwan Yoon,et al.  Stochastic comparison between simplified energy calculation and dynamic simulation , 2013 .

[15]  Fabian Ochs,et al.  The Reference Framework for System Simulations of the IEA SHC Task 44 / HPP Annex 38 Part B: Buildings and Space Heat Load , 2014 .

[16]  Jeff Haberl,et al.  Development of a home energy audit methodology for determining energy and cost efficient measures using an easy-to-use simulation: Test results from single-family houses in Texas, USA , 2016 .

[17]  Monika Woloszyn,et al.  Tools for performance simulation of heat, air and moisture conditions of whole buildings , 2008 .

[18]  Paul Strachan,et al.  Whole model empirical validation on a full-scale building , 2016 .

[19]  Jlm Jan Hensen,et al.  Mapping failures in energy and environmental performance of buildings , 2018 .

[20]  Fabian Ochs,et al.  An overview of energy district tools in Europe and the importance of an equivalent heating reference temperature for district simulations , 2017 .

[21]  Jeff Haberl,et al.  Development of a home energy audit methodology for determining energy-efficient, cost-effective measures in existing single-family houses using an easy-to-use simulation , 2015 .

[22]  Andreas H. Hermelink,et al.  CEPHEUS results : measurements and occupants' satisfaction provide evidence for Passive Houses being an option for sustainable building , 2006 .

[23]  Juan Moyano,et al.  Genetic algorithm-based approach for optimizing the energy rating on existing buildings , 2016 .

[24]  Hani H. Sait,et al.  Auditing and analysis of energy consumption of an educational building in hot and humid area , 2013 .

[25]  Eric Oliver Continuous Auditing—Taking Energy Auditing to the Next Level , 2015 .

[28]  Sture Holmberg,et al.  Evaluation of a versatile energy auditing tool , 2016 .

[29]  Constantinos A. Balaras,et al.  Infrared thermography for building diagnostics , 2002 .

[30]  Moncef Krarti,et al.  Energy Audit of Building Systems : An Engineering Approach , 2000 .

[31]  Ali F. Alajmi Energy audit of an educational building in a hot summer climate , 2012 .