Will simulation-based assessments and decisions save our built environment?

The Environment Institute Where ideas grow Assoc. Prof. Veronica Soebarto Will simulation-based assessments and decisions save our built environment?

Environment Institute Seminar Series 2009 Will simulation-based assessments and decisions save our built environment? Associate Professor Veronica Soebarto School of Architecture, Landscape Architecture and Urban Design The University of Adelaide

What is building simulation? • Modelling a building design (with computer programs) to predict how it would look, stand, perform (thermally, acoustically, visually, economically …)

Why simulate building (design)? Building simulation can: • predict future performance • diagnose existing performance to: • improve design • meet users’ requirements • optimise solutions • save energy, save $$$ • comply with the codes

Thermal & Environmental Simulation This presentation focuses on thermal and environmental simulation of building designs

Brief history • 18th century: study of heat transmission in buildings by Isaac Newton’s Scale of the degrees of heat and Jean Claude Eugène Péclet’s principles of heat flow through building elements) • Early 20th century: American Society of Heating and Ventilating Engineers, Louis Allen Harding’s heat losses by transmission through various building materials • 1940-60’s : steady state calculation • 1970’s: dynamic response of construction elements with steady state HVAC system modelling • 1980’s and beyond: dynamic integrated modelling – thermal, visual, acoustics • 1990’s: simulation used in building codes

Basic calculations The site: External environment: Shadowing Temperature Reflections Humidity Solar radiation The building: Wind Overall thermal resistance Fenestration Infiltration Internal admittance Absorptivities The occupants: Occupancy Operation schedules (eg. windows, lights, appliances) The Plant/equip: Internal environment: temperature, humidity, air Plant types movement, light efficiencies Energy consumption: heating, cooling, Schedule of ventilation, lighting, equipment operation Economic assessment: life cycle costs

Basic calculations In air-conditioned buildings: • Load calculations (heating and cooling) based on: – Heat transfers at the building envelope (eg. Q = ∑ (U x A (To – Ti)) + ∑ (SHGC x A x Total solar irradiance)*) including infiltration and ventilation – Internal heat generations (people, lights, appliances) and use patterns • Energy use calculations based on: – Load calculations – Plant equipment types, efficiency, usage (J = ∑ Q / efficiency) – Lighting and appliances types, power density, usage • Economic assessment (Life cycle costs) based on: – Energy calculations – Economic parameters (discount and inflation rates, unit prices, first costs, maintenance costs) – To calculate operating cost and total life cycle costs (PV) * in a steady state calculation only

Basic calculations In non air-conditioned buildings: • Thermal comfort ‘calculations’ based on: – Heat transfers at the building envelope – Internal heat generations and use patterns To calculate: – Indoor temperature, humidity, air flow to determine level of comfort – Using comfort models, eg. PMV, discomfort hours, adaptive models • No load and energy use calculations

Example: Improve design Work by Kent Neo Overhang – shading studies

Example: Improve design Percent of time when indoor space is within 75 70 comfort range (%) 65 60 55 50 45 40 1 2 3 4 5 6 7 8 9 10 11 12 Month Alternative 1 Alternative 2 Alternative 3

Example: Understand phenomena Modified Original Rammed earth house Effect of adding insulation to rammed earth walls on indoor temperature Soebarto, V. (2009). Using simulation to predict the indoor performance of houses using Insulated rammed earth / reverse masonry veneer rammed earth walls. Proceedings of Building Simulation 2009. IBPSA, Glasgow, 27-30 Jul.

Example: Understand phenomena 30.0 25.0 Rammed Insulated earth Temperature (degC) 20.0 15.0 10.0 Rammed earth house 5.0 0.0 1/07 1/07 2/07 2/07 3/07 3/07 4/07 4/07 5/07 5/07 6/07 7/07 7/07 8/07 8/07 9/07 9/07 10/07 10/07 11/07 11/07 12/07 12/07 13/07 14/07 14/07 outside temp C House 2 House 3 Temperature differences between rammed earth house and insulated RE house Soebarto, V. (2007). A study of the indoor thermal performance of rammed earth houses. Towards solutions for a liveable future: progress, practice, performance, people: Insulated rammed earth / reverse masonry veneer Proceedings of the 41st Annual Conference of the Architectural Science Association ANZAScA, Geelong, Australia, November 14-16 2007, Geelong, Vic., Deakin University

Example: Meet user requirements Comfort zone

Example: Meet target Will the total energy use and cost exceed the target?

Examples: Optimisation Soebarto, V. (2008). Performance assessment. In Chapter 2: Trends, Promotion and Performance. Bioclimatic Housing. Innovative Designs for Warm Climates. R. Hyde (ed.). Earthscan. P. 82.

GJ/sq.m.year 2.7 2.8 2.9 3.1 3.2 3.3 3.4 3.5 3 Status Quo Daylighting R-12 Wall Examples: Comparing solutions Natural Ventilation Double Pane Windows Energy Conservation Plan Nat-Vent & EC Plan

Example: Code compliance

Code Compliance – Energy rating • In Australia – Energy Efficiency Provisions were introduced in Building Code of Australia in 2003 (residential), 2006 (non residential) • The objective is to reduce greenhouse gas emissions (by efficiently using energy) • Residential: “A building must have, to the degree necessary, a level of thermal performance to facilitate the efficient use of energy for artificial heating and cooling and a level of water use performance to facilitate the efficient use of water” • Non residential: “A building, including its services, must have, to the degree necessary, features that facilitate the efficient use of energy appropriate to..” not only heating and cooling but also to maintain “the systems and components appropriate to the function and use of the building.” • Compliance methods: – Deemed to satisfy – Performance approach with computer simulation: • Stated value target (ie. Star rating or annual energy consumption) • Reference building

Home Energy Rating (Australia) The site: External environment: Shadowing Temperature Reflections Humidity Solar radiation The building: Wind Overall thermal resistance From weather data base Fenestration based on Standardised Infiltration Climatic Zone Internal admittance Absorptivities The occupants: Standardised user profiles and thermostat settings Internal environment: temperature Energy Loads: heating and cooling Star Rating: minimum 5 Stars

Non rating mode (temperature profiles)

Energy rating mode

Environmental Assessments • Assessing environmental performance of buildings, not just energy • Voluntary • In Australia: – Green Star (Green Building Council of Australia): • ”a comprehensive, national, voluntary environmental rating scheme that evaluates the environmental design and achievements of buildings.” (www.gbcaus.org) • built on existing systems and tools overseas (BREEAM, UK; LEED, US) and VicUrban – NABERS (National Australian Built Environment Rating System): • First developed by DEH, Utas and Exergy Australia; now managed by NSW Department of Environment, Climate Change and Water) • “a performance-based rating system for existing building”

Environmental Assessments • Green Star evaluates: • Management • Indoor Environment Quality • Energy  based on simulation/prediction, then rated with ABGR/NABERS • Transport • Water • Materials • Land Use & Ecology • Emissions • Innovation

Environmental Assessments

Environmental Assessments One Star 10 - 19 pts Two Star 20 - 29 pts Three Star 30 - 44 pts Four Star 45 - 59 pts Best Practice Five Star 60 - 74 pts Australian Excellence Six Star 75+ pts World Leader http://www.sensational-adelaide.com/index.php?Itemid=4&id=213&option=com_content&task=view http://www.designbuild-network.com/projects/tower1/tower12.html http://www.sensational-adelaide.com/index.php?Itemid=4&id=12&option=com_content&task=view

Environmental Assessments • NABERS: • For homes: energy, water • For offices: energy (ABGR), water, waste, indoor environment • For retail: energy, water (in a development stage) • Base one actual performance /records

Simulation vs Actual What we found: • Large discrepancies often occur between simulated and actual performance • Star ratings do not correlate with actual performance

Simulation vs Actual (residential) Previous studies to look at correlation between AccuRate predictions and actual heating and cooling by Williamson et al. 2001 (31 houses) and Williamson et al. 2007 (22 houses) show that there is no correlation between Star rating and energy use or GHG produced.

Simulation vs Actual (residential) Williamson, T. J., O'Shea, S., & Menadue, V. (2001). NatHERS: Science and Non-Science. In W. Osterhaus & J. McIntosh (Eds.), Proc. of 35th ANZAScA Conference. School of Architecture, Victoria University of Wellington, NZ: Australia and New Zealand Architectural Science Association.

Simulation vs Actual (residential) House 1 House 2 House 3

Simulation vs Actual (residential) HOUSE 1 HOUSE 2 HOUSE 3 STARS 3.4 Stars (of 10) 6.1 Stars 4.5 Stars Predicted heating “energy” 12.57 GJ 10.28 GJ 17.7 GJ „Actual‟ heating energy 8.93 GJ total 5.76 GJ minimal Predicted cooling “energy” 5.6 GJ 1.7 GJ 2 GJ „Actual‟ cooling energy 0 0 0 heating cooling 8.93 (TOTAL) House 1 House 1 12.57 5.6 5.76 House 2 House 2 10.28 1.7 House 3 House 3 17.7 2 0 5 10 15 20 0 5 10 15 20 Predicted 'Actual' Predicted Actual

Simulation vs Actual (Nat-Vent houses) 160 Actual Heating & Cooling (MJ/m2) 140 120 100 80 60 y = 3.3747x + 55.887 R² = 0.0115 40 20 0 0 1 2 3 4 5 6 7 Star Rating Star rating vs Actual Heating & Cooling in non AC houses* * Based on monitoring work by Soebarto (1999 – 2006)

Simulation vs Actual (Commercial) (Bannister, P. 2009. Why good buildings go bad while some are just born that way. Equilibrium, Feb., pp. 24-32)

Simulation vs Actual (Commercial) • Torcellini et al. (2004) – reviewed 6 high performance building in USA performed worse than predicted • Diamond et al. (2006) – reviewed 21 LEED certified buildings, on average 1% better than predicted but with large variability • Owens, Turner and Frankel (2008) – reviewed 121 LEED certified building, on average 25% energy savings but with large variability (25% perform worse than expected) • Abbaszabeh et al. (2006), Bunn (2007), Leaman et al. (2007), Paevere et al. (2008) – POE of green vs conventional buildings showed that green occupants have higher satisfaction in green buildings except for noise control and overall lighting Torcellini, P. A., Deru, M., Griffith, B., Long, N., Pless, S., Judkoff, R. and Crawley, D. (2004). Lessons learned from the field evaluation of six high- performance buildings. ACEEE Summer Study on Energy Efficiency of Buildings, California. Diamond, R., Opitz, M., Hicks, T., Von Neida, B. and Herrara, S. (2006). Evaluating the energy performance of the first generation of LEED-certified commercial buildings.ACEEE Summer Study on Energy Efficiency in Buildings: 3/41-3/52. Owens, B, Frankel, M. and Turner, C. The Energy Performance of LEED Buildings. National Building Institute and USGBC. Available http://www.newbuildings.org/downloads/LEED_presentation_11-13s.pdf. Accessed 18 October 2009. Abbaszadeh, S., L. Zagreus, D. Lehrer and C. Huizenga, 2006. Occupant Satisfaction with Indoor Environmental Quality in Green Buildings. Proceedings, Healthy Buildings 2006, Vol. III, 365-370, Lisbon, Portugal, June. Leaman, A., Thomas, L. and Vandenberg, M. (2007). "'Green" buildings: What Australian building users are saying." Ecolibrium vol. 6, no. No 10, pp. 22- 30. Paevere, P.*, Brown, S.*, Leaman, A.*, Luther, M. and Adams, R.* (2008) Indoor Environment Quality and Occupant Productivity in the CH2 Building, in Greg Foliente, Thomas Luetzkendorf, Peter Newton and Phillip Paevere (eds), Proceedings of the 2008 International Scientific Committee World Sustainable Building Conference (SB08), pp. 222-229, Cooperative Research Centre for Construction Innovation, Australia

Why different? DESIGN & SIMULATION • Problems in design (esp. in commercial buildings) – in reality the systems selected are not as efficient as predicted • Not all operational issues are taken into account in design and simulation • Not all appliances (plug loads) are taken into account in simulation model • Oversizing • Conflicts between many design briefs CONSTRUCTION AND COMMISSIONING • Final as-built buildings differ from the one simulated • Omission of important parts due to costs • Buildings not commissioned properly, resulting in knowledge transfer gap OPERATION • Actual occupancy different from prediction • (Experimental) technologies not perform as expected/predicted • Systems are too complex, vulnerable for errors in operation • Poor maintenance, poor operation Newsham, B. (2009). Post-occupancy evaluation of energy and indoor environment quality in green buildings: a review. NRCC-51211. National Research Council Canada Bannister, P. 2009. Why good buildings go bad while some are just born that way. Equilibrium, Feb., pp. 24-32. Bordass, B. 2009. Building performance in the age of consequences. Proceedings of Building Simulation 2009. International Building Performance Simulation Association, Glasgow, 27-30 July.

Why different? This was not taken into account St Lucia House

Suggestions DESIGN • Naturally ventilated house designs need to be assessed differently • Use profiles in the simulation need to reflect what actually happens • Conduct sensitivity analysis to see the impact of possible changes in operation CONSTRUCTION AND COMMISSIONING • Address and solve problems as described OPERATION • Address and solve problems as described

Sensitivity analysis with simulation 13000 35.0% 12000 30.0% Predicted Annual Energy Use (kWh) Difference from Base Case 11000 25.0% 10000 20.0% 9000 15.0% Base case: 8000 10.0% 5.0% 7000 Wall: R2.5 Roof: R3.5 0.0% 6000 Double glazed Temp 22-26 Temp 22-24 Window 20% Window 50% Base + Appl. Last + Appl. Temp 21-26 Temp 22-26 Temp 22-24 Window 20% Window 50% Base + Appl. Last + Appl. Temp: 21 (winter) 26 (summer) open open open open Appliances: 7.5 W/m2

Sensitivity analysis with simulation L/h=1 no overhang overhangs 200 lux 500 lux daylighting 30% 60% glazing 1 l/s/sqm 10 l/s/sqm nat ventilation 20 W/sqm 40 W/sqm lights&power 23.5 deg C 20.5 deg C AC temp +/- 3 deg C +/- 1.5 deg C AC range 10 sqm/person 8 sqm/person occ density 9-8 0.7 occupancy 9-6 full occupancy occ profile opaque blinds translucent blinds retrofit blinds @10m neighbours @ 'real' distances neighbours low-e single pane tinted single pane + hi U non-green -20% -10% 0% 10% 20% 30% 40% 50% Sensitivity range in annual emissions PEARCE, L. (2006) A systemic approach to the sensitivity analysis of the energy performance of a multi story office building. In Investigating the Roles and Challenges of Building Performance Simulation in Achieving a Sustainable Built Environment: Proceedings of the IBPSA Australasia 2006 Conference. pp 51-58.

Conclusion • Don’t believe that building design that is simulated and rated well means the building will perform well in reality. • Discrepancies between simulated/rated and actual performance do occur and can be quite significant. • Will simulation-based assessments and decisions save our built environment? Yes, but only if the problems are addressed and the following occurs after the building is built: – Fine tuning of the building systems – Continuous monitoring – Proper operation and maintenance – Educating the users.

Will simulation-based assessments and decisions save our built environment?

by University of Adelaide on Oct 23, 2009

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Will simulation-based assessments and decisions save our built environment? — Webinar Transcript

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