A multi-criteria system design optimization for net zero energy buildings under uncertainties

Abstract Net zero energy buildings (NZEBs) have been widely considered to be an effective solution to the increasing energy and environmental problems. Most conventional design methods for NZEB systems are based on deterministic data/information and have not systematically considered the significant uncertainty impacts. Consequently, the conventional design methods lead to popular oversized problems in practice. Meanwhile, NZEB system design methods need to consider customers’ actual performance preferences but few existing methods can take account of them. Therefore, this study proposes a multi-criteria system design optimization for NZEBs under uncertainties. In the study, three performance criteria are used to evaluate the overall NZEB system performance based on user-defined weighted factors. Case studies are conducted to demonstrate the effectiveness of the proposed method.

[1]  Maureen Hand,et al.  IEA Wind Task 26: The Past and Future Cost of Wind Energy, Work Package 2 , 2012 .

[2]  Christina J. Hopfe,et al.  Uncertainty and sensitivity analysis in building performance simulation for decision support and design optimization , 2009 .

[3]  Refrigerating.  ASHRAE handbook and product directory /published by the American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc , 1977 .

[4]  Jlm Jan Hensen,et al.  Uncertainty analysis in building performance simulation for design support , 2011 .

[5]  P. Torcellini,et al.  Zero Energy Buildings: A Critical Look at the Definition; Preprint , 2006 .

[6]  Ery Djunaedy,et al.  Oversizing of HVAC system: Signatures and penalties , 2011 .

[7]  Refrigerating.  ASHRAE handbook of fundamentals , 1967 .

[8]  Shan K. Wang,et al.  Handbook of Air Conditioning and Refrigeration , 1993 .

[9]  Brian Anderson,et al.  Uncertainty in the thermal conductivity of insulation materials , 2010 .

[10]  Alan Goodrich,et al.  Photovoltaic (PV) Pricing Trends: Historical, Recent, and Near-Term Projections , 2014 .

[11]  Jin-Sung Lee,et al.  Development of Integrated Operation, Low-End Energy Building Engineering Technology in Korea , 2008 .

[12]  B. W. Ang,et al.  Decision analysis in energy and environmental modeling , 1995 .

[13]  Arthur A. Bell,et al.  HVAC Equations, Data and Rules of Thumb , 2000 .

[14]  M. Kummert,et al.  Designing net-zero energy buildings for the future climate, not for the past , 2012 .

[15]  Macedon Moldovan,et al.  Improving the renewable energy mix in a building toward the nearly zero energy status , 2014 .

[16]  P. Torcellini,et al.  Getting to Net Zero , 2009 .

[17]  Jaume Salom,et al.  Understanding net zero energy buildings: Evaluation of load matching and grid interaction indicators , 2011 .

[18]  W. Grondzik.  Air Conditioning System Design Manual , 2011 .

[19]  J. D. Balcomb,et al.  Multi-criteria decision-making process for buildings , 2000, Collection of Technical Papers. 35th Intersociety Energy Conversion Engineering Conference and Exhibit (IECEC) (Cat. No.00CH37022).

[20]  Daryl R. Myers,et al.  Solar Radiation Modeling and Measurements for Renewable Energy Applications: Data and Model Quality , 2004 .

[21]  Phillip John Jones,et al.  Case study of zero energy house design in UK , 2009 .

[22]  Eric Lantz,et al.  WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy , 2013 .

[23]  W Wim Zeiler,et al.  Net-zero energy building schools , 2013 .

[24]  L. Phillips,et al.  Multi-criteria analysis: a manual , 2009 .

[25]  Elias B. Kosmatopoulos,et al.  A roadmap towards intelligent net zero- and positive-energy buildings , 2011 .

[26]  Eike Musall,et al.  Zero Energy Building A review of definitions and calculation methodologies , 2011 .

[27]  Jose Manuel Cejudo-Lopez,et al.  Uncertainty in peak cooling load calculations , 2010 .

[28]  Kevin J. Lomas,et al.  Sensitivity analysis techniques for building thermal simulation programs , 1992 .

[29]  Godfried Augenbroe,et al.  Analysis of uncertainty in building design evaluations and its implications , 2002 .

[30]  Yu Wang,et al.  HVAC system design under peak load prediction uncertainty using multiple-criterion decision making technique , 2015 .