Using climate change data for building simulation

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1 Using climate change data for building simulation Seth Holmes, AIA, LEED AP July 12, 2011 Climate change and the building industry Simulating Climate Change Current research

2 Using climate change data for building simulation Seth Holmes, AIA, LEED AP July 12, 2011 Climate change and the building industry Simulating Climate Change Current research Keeling Curve: CO 2 levels since 1958 Similar for Temperature Similar for GHG Emissions Projections for Boston: Shifting timing of seasons Increased drought potential Sea level rise of up to 37 inches Increased storm and rainfall intensity Average Temperature change from +6 F to +14 F Average days over 100 F, from 1 to between 6 & 24 Source: A report of the Northeast Climate Impact Assessment. Union of Concerned Scientists, 2006

3 What has been done about it?

4 What do we do? Mitigation (reduce our emissions) Adaptation (live with the effects)

5 Climate Change Efforts in the building industry = Mitigation Focus Cottonwood Development, Holladay Utah Net-Zero Energy Design High Performance Codes Smart Growth Development Green Rating systems

6 What about Adaptation? Observed and modeled global temperature increase Adaptation at the expense of mitigation Source: IPCC Fourth Assessment Report, Working Group 1, The Physical Science Basis, Figure 1.1

7 Simulating Climate Change

8 What weather file to use for long range building simulation? Adaptive Capacity?

9 enable designers to assess the impact of climate change on their designs using building energy and thermal simulation models. enable designers to develop strategies through which buildings can be adapted to cope with the impacts of future climate change, for example warmer summers. Hacker, J., Capon, R., Mylona, A. (2009). Use of climate change scenarios for building simulation: the CIBSE future weather years. The Chartered Institution of Building Services Engineers, London, UK. CIBSE TM48: 2009.

include: winds, heat transfer, radiation, relative humidity, and surface hydrology, etc. Earth divided into Horizontal and Vertical cells.

10 Climate Change Models How is future climate and subsequent temperatures determined? 1. General Circulation Models Numerical / mathematical models Based on physics, fluid motion, and chemistry of the planet systems Results include: winds, heat transfer, radiation, relative humidity, and surface hydrology, etc. Earth divided into Horizontal and Vertical cells. Cell resolutions continues to shrink as research progresses Image Source: Image Source: IPCC Fourth Assessment Report on Climate Change

emissions Scenario driving forces include: Population, Economic and social development Energy and Technology, Agriculture and Land Use, Policy SRES Scenarios (2000) +

11 Climate Change Models 2. Emissions Scenarios Socio-economic futures for the planet; subdivided by regions Based in historical data and consistent assumptions Used to determine GHG and aerosol emissions Scenario driving forces include: Population, Economic and social development Energy and Technology, Agriculture and Land Use, Policy SRES Scenarios (2000) + IPCC 3 rd Assessment Report (TAR 2001) Used for 3 rd and 4 th IPCC assessment report (TAR & AR4) Divided into 4 main Storylines with sub-groups Commonly used subgroups: A1FI, A2, B1, B2 A1FI group represents Fossil Intensive group Image Source: IPCC 3 rd Assessment Report Image Source: IPCC Special Report on Emissions

12 Generating hourly weather data CIBSE: 4 analyzed procedures 1. Dynamical downscaling 2. Analogue scenarios 3. Time series adjustment ('morphing') 4. Stochastic models ( weather generator ) TMY + Weather file HadCM3 Source: CIBSE TM48

13 Morphing results Adaptive Capacity?

14 Morphing results Adaptive Capacity?

indoor environment: impacts and adaptation Concluded that it is possible to provide reasonable

15 How are buildings impacted? - CIBSE climate change building modeling efforts CIBSE - TM-36: 2005 Climate change and the indoor environment: impacts and adaptation Concluded that it is possible to provide reasonable conditions in many classes of buildings without incurring large increases in energy using good passive design principles with supplementary mechanical cooling where needed.

16 Current Research

17 $

18 What about climate change and energy prices? 60% H.R Waxman / Markey (2009) Electricity Price Increase 50% Price Increase 40% 30% 20% 10% Price Increase 0% 60% 50% 40% 30% 20% 10% 0% -10% Natural Gas Price Increase Adage NBCC MIT-Med MIT-Full Data Source: Economic Insights from Modeling Analyses of H.R the American Clean Energy and Security Act (Waxman- Markey); Pew Center for Global Climate Change

19 Image Source: 2degrees_canute.jpg

20 What about combined Temperature and Energy Price impacts? 60% Electricity Price Increase 50% Price Increase 40% 30% 20% 10% Price Increase 0% 60% 50% 40% 30% 20% 10% 0% -10% Natural Gas Price Increase Adage NBCC MIT-Med MIT-Full Source: IPCC Fourth Assessment Report, Working Group 1, The Physical Science Basis, Figure 1.1 Data Source: Economic Insights from Modeling Analyses of H.R the American Clean Energy and Security Act (Waxman- Markey); Pew Center for Global Climate Change

21 Climate change risk from a building owner s perspective : Assessing future climate and energy price scenarios Research Questions: How can climate change temperature and energy price modeling inform long term building design and investment decisions? How will climate change driven temperature energy price impacts affect the life-cycle operational costs of buildings in the U.S.? Objective: To develop an analysis method and tool that introduces climate change and energy price predictions to the financial analysis of new building construction or retrofit projects. A. Methodology B. Boston case study

22 Methodology

23 Methodology

Building baseline energy use Whole building energy model How is future energy use in a building typically calculated? 1.

Whole Building Energy Model (new or renovated building Whole building energy model Mimic all heat flows in a building and

Green rating system, code compliance, energy use projections Inputs Required a) Geometric model, Materials, Schedules, Loads

24 Building baseline energy use Whole building energy model How is future energy use in a building typically calculated? 1. Historical use data (existing building) 2. Whole Building Energy Model (new or renovated building Whole building energy model Mimic all heat flows in a building and predict building energy use and interior comfort conditions. Green rating system, code compliance, energy use projections Inputs Required a) Geometric model, Materials, Schedules, Loads b) Weather data is critical based on typical data from 30 year period DOE provides EPWs globally (energy plus weather file) TMY3 = ; TMY2 = ; TMY = Process Establish baseline building design & model Create upgrade designs for simulation and comparison

Run program for 4 reference scenarios: A1FI, A2, B1, B2 (A1FI, B1, B2 HadCM3 data same format

25 Create climate change weather files Weather File Morphing Process 1. Select TMY2, 1990 baseline file (same timeframe as TAR) 2. Run program for 4 reference scenarios: A1FI, A2, B1, B2 (A1FI, B1, B2 HadCM3 data same format as A2, so these files can be morphed similarly to the A2 files) 3. Output 3 future TMY files for 4 climate scenarios = 12 total TMY2.EPW + = Weather file HadCM3

26 Simulate life-cycle energy use Combine future weather files in building energy model Process 1. Simulate building using Baseline and Morphed climate change weather files. 2. Linear interpolation between Baseline and Morphed simulation results (1990, 2020, 2050, 2080) 3. Remove data prior to A1FI X A2 B1 B2

27 Combine climate change energy prices Climate Change Emissions Scenarios SRES (2000) Background Energy prices are embedded in scenario and subsequent modeling Price data available is only at the wholesale level Prices are not policy specific Prices not usable for this study Energy Modeling Forum EMF-22 (2009) US Transition Scenarios for (reference, 287,203,167) Study illustrates effect on costs due to emissions reduction goals for 2050 Data available for end use energy prices (gas, electric, oil) at a national level through 2050 Prices vary greatly depending on model and emissions pathway 6 models utilized; some with multiple versions EMF-22 Emissions Pathways Image Source: Overview of EMF-22 US transition scenarios (Fawcett 2009)

for cooling energy, while natural gas use for heating is steadily on the rise (EIA 2006).

28 Combine climate change energy prices Heating vs. Cooling Energy assumptions Electricity for all cooling requirements EMF-22 US Energy Price Models Natural gas use for all heating requirements 98% of commercial buildings in the US use electricity for cooling energy, while natural gas use for heating is steadily on the rise (EIA 2006). Process There are Seven EMF-22 models selected because they had complete pricing data from in 10 year increments (2010, 2020, 2030, 2040, 2050) EMF-22 US Example end-use energy cost data For each model, 2010 energy prices are multiplied by a factor to match the 2010 commercial energy prices for the location of the building project Each subsequent 10 year price also multiplied by that factor (2020, 2030, 2040, 2050) Prices for are flat, using 2050 prices. Observation Electricity costs increase more than natural gas in 6 out of 7 EMF-22 models (Arrows at right)

Combine climate change energy prices Linking SRES and EMF 22 models Radiative Forcing Primary metrics in climate change modelling Definition: the change in the net vertical irradiance at the

29 Combine climate change energy prices Linking SRES and EMF 22 models Radiative Forcing Primary metrics in climate change modelling Definition: the change in the net vertical irradiance at the tropopause (expressed in Watts/square metre) (Cubasch 2001). Changes to radiative forcing levels can occur from a variety of events including increased GHG or aerosol emissions as well as increased solar gain from solar flares. The IPCC measures radiative forcing relative to preindustrial conditions defined for Process SRES / TAR scenarios matched to an EMF-22 scenario based on closest radiative forcing level One Worst Case Scenario combined scenario is created (A1FI / 167) to represent highest temperatures and higtest prices from both TAR and EMF-22 Resulting combined scenarios are referred to as Temperature+Price scenarios

30 Energy cost comparison Investment analysis Economic comparison metrics 1. Change in constant dollar total and annual energy costs 2. Payback Period, in years, for each design upgrade cost in comparison to a baseline design 3. Internal Rate of Return (IRR) calculation for each design upgrade value for period; This is a profitability measure that compares investment cost to positive cash flow for a fixed period Cash flows in this study = $ savings achieved by each building upgrade design Each metric calculated for each Temperature+Price scenarios to compare range of financial risk or opportunity. Baseline Design X Upgrade Design 1 Upgrade Design 2 Etc

31 Case Study

32 Case Study Building type and Location Hypothetical Case Study Building owner has existing 1980 era office building. Building located in Boston, Massachusetts HVAC needs replacement Owner want to determine long term energy usage and cost in order to budget appropriate building operations funds Owner wants to compare existing building projected costs with three design options 1. Traditional Cooling system (sealed windows) 2. Mixed Mode Cooling system (operable windows with natural ventilation control) 3. Mixed mode with better insulation Traditional Cooling Image Source: Union of Concerned Scientists, 2006 Mixed Mode Cooling Image Source: UC Berkeley, CBE

33 Case Study DOE Reference Office Building (Mid-Size) $89,000 upgrade cost $183,000 upgrade cost Building design options Baseline ~54,000 sq ft office building Built to 1980 energy code compliance / traditional envelope building practices VAV system with gas terminal reheat (DOE modeled reheat system changed from electric to gas for this study) DX cooling system is electric; Gas furnace for heating All heating = gas; all cooling = electric Minimum Upgrade Same as Baseline, except: 1. Envelope and mechanical built to ASHREA standard 2. Window SHGC and insulation slight improvements Medium Upgrade Same as Minimum, except: 1. Hybrid cooling function added to open windows and stop HVAC when setpoints are achievable with outside air 2. 50% of window area opens for Hybrid natural ventilation 3. Horizontal solar shading on South façade, vertical on East & West Advanced Upgrade Same as Medium, except: 1. Thermal insulation in roof and walls is doubled $255,000 upgrade cost (All costs calculated using RS Means 2010)

34 Case Study Simulation Model

35 Case Study Results - 1 Simulation and Life-Cycle Energy use example Baseline building TMY2 Baseline temperature TAR A1FI scenario

Case Study Results - 2 Comparing cost projection techniques Price scenarios added to energy use Error bars indicate range of 4 Temperature+Price scenarios For the all four designs, cumulative cost

36 Case Study Results - 2 Comparing cost projection techniques Price scenarios added to energy use Error bars indicate range of 4 Temperature+Price scenarios For the all four designs, cumulative cost changes compared to the conventional method (static climate and price). For Temperature only analysis: cost changes from -1% to12% For Temperature+Price Scenarios: cost changes from 15% to 68% Massachusetts 2010 Energy Prices Electricity = $0.1375/kWh Natural Gas = $ /GJ

Case Study Results - 3 Investment analysis

For Temperature+Price Scenarios: Payback

37 Case Study Results - 3 Investment analysis For Temperature only analysis: Payback periods = range from 13 to 19 years, IRR = range from 6.7% to 9.3%. For Temperature+Price Scenarios: Payback periods = range from 12 to 18 years, IRR = range from 7.0% to 10.5%.

38 Case Study Results - 5 life-cycle analysis example

Results Analysis Compared to method that ignores emissions price variables Long term energy costs have greater increases and variation among

Boston case study Minimum design most cost effective (payback and IRR) Payback periods greater than 10 years may be too high for developers;

39 Results Analysis Compared to method that ignores emissions price variables Long term energy costs have greater increases and variation among scenarios More efficient designs produce less variation Payback times shorter for all upgrade designs IRR higher for all upgrade designs Boston case study Minimum design most cost effective (payback and IRR) Payback periods greater than 10 years may be too high for developers; institutions may consider this acceptable Big factor: Electricity price increase in tandem with electric cooling increase dramatically raise costs.

40 Discussion and Conclusions Research Questions: How can climate change temperature and energy price modeling inform long term building design and investment decisions? How will climate change driven temperature energy price impacts affect the life cycle operational costs of buildings in the U.S.? Research Application: Building energy simulations can be linked with climate change temperature impacts and energy cost analyses using existing tools and datasets Building owners minimize risk to increased operations costs. Building owners may make better-informed investment decisions Pinpoint design options most sensitive to climate change consider a different energy source for cooling needs due to the increases in electricity prices. Agrees with other research suggesting mixed mode design as a climate change adaptation design method. Potential new metric or analysis method for sustainable rating systems Limitations Multiple sources for temperature and price data Outdated climate temperature data (TAR vs AR4) EMF-22 prices are national, not regional Single location analyzed Does not consider peak loads and mechanical system longevity Only a few building design and efficiency measures analyzed

41 Fin

42 How much does mitigation cost? U.S. Mid-Range Cost Abatement Curve to 2030 (McKinsey 2007) Improving energy efficiency in buildings and appliances megatons (midrange) to 870 megatons (highrange). This large cluster of negative-cost options includes: lighting retrofits, improved heating, ventilation, air conditioning systems, building envelopes, and building control systems. Source: Reducing U.S. Greenhouse Gases: How much at what cost? (McKinsey&Company, December 2007)

CLIMATE CHANGE RISKS FROM A BUILDING OWNER S PERSPECTIVE: ASSESSING FUTURE CLIMATE AND ENERGY PRICE SCENARIOS

CLIMATE CHANGE RISKS FROM A BUILDING OWNER S PERSPECTIVE: ASSESSING FUTURE CLIMATE AND ENERGY PRICE SCENARIOS Seth H. Holmes and Christoph F. Reinhart Harvard University Graduate School of Design, Cambridge,