environmental performance simulation · 2013. 6. 20. · 1 christoph reinhart barcelona global en...

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Christoph ReinhartBarcelona Global Energy Challenges Energy in Buildings and Cities – June 13 2013

Christoph ReinhartBarcelona Global Energy Challenges Energy in Buildings and Cities – June 13 2013

Environmental Performance Simulation From evaluating performance to suggesting new formsfor buildings and neighborhoods

Massachusetts Institute of TechnologyDepartment of ArchitectureBuilding Technology Program

Simulation Games

Urban Scorecard

Climate Change and Finance

Cambridge Solar Map

DIVA

“Our research goal is to change current sustainable design practice by developing, validating and testing workflows and metrics that lead to

improved design solutions as far as occupant comfort and health as well as building energy use are concerned. The premise of this work is that an

informed decision is a better decision.”

Sustainable Design Lab @ MIT

Carlos Cerezo Karthik DondetiTimur DoganDiego Ibarra (GSD)Kristian FennessyAlstan JakubiecNathaniel JonesChristoph ReinhartKrista PalenJohn SullivanTarek RakhaZahraa Saiyed

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Natural Resources Canada

Our work has been supported by

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Solar Buildings1978

Two-storey sunspaceThermal massActive air circulation 83% solar heated

Balcomb Residence, Santa Fe, NW (around 1978)Photo taken from Lechner, Sun Wind and Light

Green Buildings1991

South-exposed half cylinderAir-to-ground heat exchangerVentilation-heat-recoverySolar Hot WaterPhotovoltaics 4.2kWpeak

Transparent insulating panelsFuel cells and hydrogen tanks

Self-sufficient solar house Freiburg, 1991Architecture: Planerwerkstatt Hölken & Berghoff

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Green Buildings2007

‘Made in Germany’, triple glazing, Phase Change Materials, exterior wooden shutters, PV on the roof, integrated lighting system, clear architectural forms

Solar Decathlon Winner 2007 (Team Germany)Photo taken from flckr.com

Basic Hypothesis

Saving energy in the building sector has largely become an issue of system integration and

information sharing.

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Building Performance SimulationBuilding Performance Simulation: An computer-based attempt to model the various energy and mass flows within a building in order to predict one or several performance aspects of a design.

Operational EnergyOperational Energy Solar RadiationSolar Radiation DaylightDaylight

Return on InvestmentReturn on Investment Occupant ComfortOccupant Comfort WalkabilityWalkability

Today’s PresentationFrom evaluating performance to

suggesting new forms

Environmental performance simulations are now capable of predicting the physical performance of commonly used building typologies and technologies.

Parts of this analysis can be done by architects and planners themselves. Is this true/desirable?

How can we make sure that designers are using the tools accurately and effectively?

We are now moving toward whole city energy models in which different energy flows are monitored are optimized.

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Why Environmental Performance Simulation?

To demonstrate code compliance and to reduce risk.

To compare different design variants.

Do today’s simulation programs work?

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ASHRAE thinks so.

ASHRAE 140 -2007 Standard Method for the Evaluation of Building Energy Analysis Computer Programs

Purpose of the Standard

Analyzing and diagnosing buildingenergy simulation software usingsoftware-to-software and software-to-analytical-solution comparisons.

Checking a program against a previousversion of itself after internal codemodifications such as an algorithmicchange.

Uncle Sam thinks so, too.

Tax Deduction Information

Under IRS rules, taxpayers' building energy use performance must be calculated using software that has been tested according to ANSI/ASHRAE Standard 140 to qualify for tax deductions.

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“I have heard that LEED certified buildings, which are designed based on

BPS, do often not save as much energy as predicted by the simulation.”

Energy Performance of LEED BuildingsNew Buildings Institute (NBI) Study (2008)

For all 121 LEED buildings the median measured EUI was 24% below the CBECS national average [for 2003].

www.gbci.org/ShowFile.aspx?DocumentID=3598Note: 552 LEED-NC buildings were certified in 2006

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Performance of LEED Buildings

LEED buildings have on average a 30% lower EUI (Energy Use Intensity).

A third of LEED buildings had a higher EUI than their matched CBEC

counterpart.

LEED‐NBI data, CBECS matching by Newsham et al, 2009 Figure from Daylighting Handbook (Reinhart)

“If the energy use of LEED buildings can be so high, did the computer simulations

predict this?”

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Comparison of measured and simulated energy use for 97 LEED Buildings

PaperH W Samuelson, A Lantz and C F Reinhart, "Non-technical barriers to energy model sharing and reuse", Buildingand Environment, 54, pp. 71-76, 2012.

Model uncertainty from weather, infiltration rate, usage scheduleand occupant behavior.

But, models can be calibrated…

PhD thesis H W Samuelson (Harvard GSD, May 2013)

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Need for Commissioning

Source USGBC; Figure from Daylighting Handbook (Reinhart)




Parts of this analysis can be done by the designers themselves. Is this true/desirable?



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Teaching Modeling

SimulationChecklist

Book Chapter: Reinhart C F, “Simulation-based Daylight Performance Predictions“ in Building Performance Simulation for Design and Operation, Editors J Hensen and R Lamberts, Taylor & Francis, 2011

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Spring 2012 MIT 4.430 Daylighting

Spring 2012 MIT 4.430 Daylighting

Simulation of 10.485. Practicing good simulation habits. Building trust in one’s own modeling skills.

Paper: Ibarra D, Reinhart C F, "TEACHING DAYLIGHT SIMULATIONS – IMPROVING MODELING WORKFLOWS FOR SIMULATION NOVICES”, Proceedings Building Simulation 2013

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How do we reach the architects not interested in taking electives on

simulation?

Question to Architects: “How frequently do simulation results influence the design of your buildings?”

PaperH W Samuelson, A Lantz and C F Reinhart, "Non-technical barriers to energy model sharing andreuse", Building and Environment, 54, pp. 71-76, 2012.

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The Game …

Human Cluster [Experts] Simulation Queue

Searching for the winning combination…

C F Reinhart, T Dogan, D Ibarra and H W Samuelson, "Learning by doing - Teaching energy simulation as a game", Journal of Building Performance Simulation, October 2011.

Simulation Order Form

Provided by Modeler

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EUIs of the 10 final designs were 22–31% below the base variant. Building massings chosen by the different groups diverged

significantly revealing that a performance based design analysis does not necessarily lead to converging architectural solutions.

Results: Final Designs







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Great, I am ready to try this, which performance metrics shall I use to

improve my daylighting/passive design?

Definition of a ‘well daylit space’A space that is primarily lit with natural light and that combines a high occupant satisfaction with the visual and thermal environment with low overall energy use for lighting, heating and cooling.

Paper: C F Reinhart and J Wienold, "The Daylighting Dashboard - A Simulation-Based Design Analysisfor Daylit Spaces", accepted for publication in Building and Environment, 2010.

Figure from Daylighting Handbook (Reinhart)

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Daylighting Dashboard

Paper Reinhart C F, J Wienold, “The Daylighting Dashboard - A Simulation-Based Design Analysis for Daylit Spaces”. Building andEnvironment, 2011 46:2 386-396

Daylit Area: 73% of the space 44% of the space

% Occupied hours

Potential glare: 50% of the year no glare View: 100% 50%

Question: Should I specify blinds or not?

DIVA for Rhino

Paper: K Lagios, J Niemasz and C F Reinhart, "Animated Building Performance Simulation (ABPS) - Linking Rhinoceros/Grasshopper with

Radiance/Daysim", Proceedings of SimBuild 2010, New York City, August 2010 J A Jakubiec and C F Reinhart, DIVA-for-Rhino 2.0: Environmental parametric modeling in Rhinoceros/Grasshopper using

Radiance, Daysim and EnergyPlus, Proceedings of Building Simulation 2011, Sydney, November 2011

Rhino ModelRhino Model

Climate‐based MetricsClimate‐based MetricsDaysimDaysim

Thermal LoadsThermal LoadsEnergyPlusEnergyPlus

Annual Glare MapsAnnual Glare MapsDaysimDaysim

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So, now that we have an analysis framework for daylighting. Let’s design something.

DIVA for Rhino

Radiation MapsRadiation MapsClimate‐based MetricsClimate‐based MetricsVisual ComfortVisual ComfortRadianceRadiance

Rhino ModelRhino Model

Paper: K Lagios, J Niemasz and C F Reinhart, "Animated Building Performance Simulation (ABPS) - Linking Rhinoceros/Grasshopper with

Radiance/Daysim", SimBuild 2010, New York City, August 2010 J A Jakubiec and C F Reinhart, DIVA-for-Rhino 2.0: Environmental parametric modeling in Rhinoceros/Grasshopper using

Radiance, Daysim and EnergyPlus, Building Simulation 2011, Sydney, November 2011

Annual Glare MapsAnnual Glare Maps Thermal LoadsThermal Loads

GrasshopperGrasshopper

VisualizationsVisualizationsEvalglalreEvalglalre DaysimDaysim GenCumulativeSkyGenCumulativeSky DaysimDaysim EnergyPlusEnergyPlus

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Animated Building Performance Simulation

Simulation: J Niemasz and K Lagios

Zollverein by SAANA

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Environmental Performance combined with a Genetic Algorithms

Determine a box shape with maximum enclosed volume and annual solar radiation exposure in Boston (Niemasz)

This looks a bit like trying to have monkeys play Shakespeare. Can we do better?

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SHADERADE - Generating the Next Generation of Shading Systems

Design: Jeff Niemasz

Conventional Shading SHADERADENon Performing Shading

How to Design a Static Shading System

Step 1 Identify the cooling period

Solstices Heating vs. Cooling Degree Days Hourly Load Profile

Mar 21 – Sep 21

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How to Design a Static Shading System

Step 2 Find a form that shades my window during cooling period

2 dimensional method Autodesk Ecotect

Static Exterior Shading: SHADERADE

Surround Shade

Paper: J Sargent, J Niemasz, C F Reinhart, “SHADERADE: Combining Rhinoceros and EnergyPlus for the design of static exterior shadingdevices”, Building Simulation 2011, Sydney, November 2011.

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Surround Shade

Once the volume has been assessed, any surface within its bounds can be visualized:


Surround Shade

Trimming away regions with negative value (cutoff = 0):

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Horizontal and surround shades

Load optimized, 85% value trim:

Anchorage Boston Phoenix

Horizontal and surround shades,

Carbon optimized, 85% value trim:


Anchorage Boston Phoenix

(COP of 1.67, 0.83 for cooling, heating; carbon equivalent factors of 0.232, 0.758 kg/kWh for gas , electricity)

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Recent Developments

J Sargent & J Niemasz

Future Price ScenariosS Holmes, C Reinhart

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A General Circulation Model (GCM) is a mathematical model of the general circulation of a planetary atmosphere or ocean. [Wikipedia]

The IPCC Working Group III developed storylines which represent a potential range of different demographic, social, economic, technological and environmental developments (IPCC 2000).

Climate Change Predictions

Climate Change Weather File Generator

Generates future climate files for locations worldwide (with limitations) with a specific focus on the UK. It is based on the ‘morphing’ methodology.

Belcher SE, Hacker JN, Powell DS. Constructing design weather data for future climates. Building Services Engineering Research and Technology 2005; 26 (1): 49-61.Jentsch MF, Bahaj AS, James PAB. Climate change future proofing of buildings - Generation and assessment of building simulation weather files. Energy and Buildings 2008; 40 (12): 2148-2168.

http://www.serg.soton.ac.uk/ccworldweathergen/index.html

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How large is the Effect?

Harvard University – Gund Hall DesignBuilder model

Gund Hall now 33 Zone E+ model 1990 TMY2 weather data for Boston

Samuelson, Holmes, Reinhart 2011

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Case Study: Gund Hall now and then 33 Zone E+ model 1990 TMY2 weather data for Boston predicted 2080 weather data for the IPCCCA2 scenario (medium to high emissions scenario).

36% less heating

45% more cooling

Linking Future Climate Files with Future Prices

The basic idea of the paper is to link 7 of the 22 energy price projections from the 2009 Energy modeling Forum (EMF-22) to the four climate change projections from the 3rd IPCC Assessment Report (TAR).

The matching is realized via the Radiative Forcing (RF) of the different scenarios. RF is the change in net irradiance at the top of the tropopause compared to the year 1750.

Data Source: Economic Insights from Modeling Analyses of H.R. 2454 — the American Clean Energy and Security Act (Waxman-Markey); Pew Center for Global Climate Change

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Case Study: Office Building in BostonGeneric 1980s office building, floor area 5000m2, 3 stories. Baseline: Building left as is.

Minimum: Upgrade so that the building meets ASHREA 90.1-2004 (more efficient HVAC and windows (inoperable).

Medium: Same as previous but add mixed-mode ventilation & solar shading.

Advanced: Same as previous but double all insulation levels.

$89,000

upgrade ∆ cost

$183,000

upgrade ∆ cost

$255,000

upgrade ∆ cost

Case Study: Cumulative Energy Costs

Paper: S H Holmes and C F Reinhart, Assessing future climate change and energy price scenarios for institutional building investment and HVAC operation, Building Research and Information, 41:2, pp. 209-222, 2013.

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Case Study: Cumulative Energy Costs

IRR highest for minimum upgrade. (It is tough, energy is cheap in this country.)

Cooling dominated climates have higher IRRs. This does not necessarily translate into actions today.







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Urban ModelingC Reinhart, J A Jakubiec, T Dogan, T Rakha

“In 2008, the world reached an invisible but momentous milestone: For the first time in history, more than half its human population

[…] was living in urban areas. In 2050 there will be 9 billion people.”

United Nations Population Fund

Why should we care about energy use in cities?

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Solution 1: Let them figure it out themselves.

Informal Settlement in Rio

Question: How to house 1.7 Billion City Dwellers in 17 Years?

Suburbs in Shanghai

Solution 2: Dense new construction.

First combination of LiDAR data with advanced building simulation modules

Cambridge Solar Map

http://www.cambridgema.gov/solar/

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Photo of the MIT Campus (Google Maps).

LiDAR Data of the MIT Campus

3 dimensional point cloud (126 million points).

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GIS Model of Cambridge

City ArcGIS model: Building Footprints, Exterior Cladding Materials, Ground Composition, Appraised Value and Renovations, Number of Floors, Building Type, Number of Bedrooms, Year of Construction

3D Model of the MIT Campus

Generation of a 3D model through surface triangulation.

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Solar Radiation Map

Cumulative annual solar radiation.

Impact of Roof Temperature on Solar Cell Efficiency

Paper: A Jakubiec and C F Reinhart, A Method for Predicting City-Wide Electricity Gains from Photovoltaic Panels Based on LiDAR and GIS Data Combined with Hourly DAYSIM Simulations, Solar Energy (in press)

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2008 - 2011

Cambridge Solar Map

http://www.cambridgema.gov/solar/

How accurate are the results?

Paper: A Jakubiec and C F Reinhart, A Method for Predicting City-Wide Electricity Gains from Photovoltaic Panels Based on LiDAR and GIS Data Combined with Hourly DAYSIM Simulations, Solar Energy (in press)

Annual Error 3.6% Annual Error 5.3%

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(1) Get your Roof’s Solar Potential

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If we were up to the challenge we could generate a third of the city’s electricity use via PV.

The cost would be in the order of $US 2.8 billion.

PV Potential for Cambridge

Umi is a new urban modeling platform to design and improve new and existing neighborhoods regarding multiple measures of urban sustainability including operational energy use, daylighting, outdoor comfort and sustainable transportation.

Various effort are currently supported by: National Science Foundation US Department of Energy MIT Energy Initiative Transsolar Climate Engineering Government of Kuwait

Urban Modeling

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Umi Workflow

www.urbanmodeling.net

Rhino Model

1 Landmark building with explicit mixed land-use2 Residential block and single family housing units3 Irregular courtyard composition with massive block4 Row houses (in a straight line) 5 Park6 Massing composition7 Narrow courtyard complex with a relative hi-rise 8 Explicit mixed land use with wider courtyard9 Widest courtyard with low-rise arrangement

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Umi- Energy

Paper: C F Reinhart T Dogan, J A Jakubiec, T Rakha, A and A Sang, “UMI – An urban simulation environment for building energy use, daylighting and walkability”, Building Simulation 2013, Chambery, France, August 2013.

Umi- Daylight

Paper: T Dogan, C F Reinhart and P Michelatos, “Urban daylight simulation: Calculating the daylit area of urban designs”, Proceedings of SimBuild 2012, Madison, Wisconsin, USA.

Hourly Exterior Solar Radiation (Daysim)

Interior light solver

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Umi- Daylight

Paper: T Dogan, C F Reinhart and P Michelatos, “Urban daylight simulation: Calculating the daylit area of urban designs”, Proceedings of SimBuild 2012, Madison, Wisconsin, USA.

Computed in Less than 30 minutes

Umi- Outdoor Comfort

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Umi- Mobility

Paper: T Rakha and C F Reinhart, “A carbon impact simulation-based framework for land use planning and non-motorized travel behavior interactions”, Submitted to Building Simulation 2013, Chambery, France, August 2013.

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Example in UmiPassivHaus Neighborhood

Umi- Transportation

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Umi- Transportation

Umi- Finance

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Scorecard

Closing Thoughts

Modern simulation engines can provide more actionable information for energy saving measures to building owners, designers and planning boards.

More comprehensive teaching of these tools is required. One-day workshop can only each individuals how to “press buttons”. It takes at least a term to appreciate how the BPS may truly inform design.

We need new and more good performance metrics.

Soon we will see whole city energy models in which different energy flows are monitored are optimized.

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Thank YouContactChristoph ReinhartAssociate Professor Massachusetts Institute of TechnologyEmail: [email protected]

MIT Sustainable Design LabCarlos CerezoKarthik DondetiTimur DoganDiego Ibarra (GSD)Alstan JakubiecTarek Rakha John Sullivan

Solemma LLCAlstan JakubiecKera LagiosJeff NiemaszJonnie Sargent

mapdwell LLCEduardo BerlinAlstan Jakubiec

AlumniSeth Holmes, Elliot Glassman, Cynthia Kwan, Rohit Manudhane, Rashida Mogri, AzadehOmidfar, Debashree Pal, Tiffany Otis, Holly W Samuelson, Devon Sparks, Jennifer Sze

environmental performance simulation · 2013. 6. 20. · 1 christoph reinhart barcelona global en...

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