Modeling, It's Not Just For Calendars and Energy

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Nathan Kegel of IES presents Modeling, It's not Just for Calendars and Energy at the 2012 Chicago Energy Modeling Conference.

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Modeling, It's Not Just For Calendars and Energy

  1. 1. ModelingIt’s not Just for Calendars and Energy Nathan Kegel ASHRAE Member, LEED AP BD+C Project Manager Business Development Manager Nathan.kegel@iesve.com www.iesve.com
  2. 2. Learning Objectives:• Understand What a Model Is• Understand Different Types of Models for Buildings• Understand the difference between BIM and BAM and how to use them in practice• Understand traditional, current, and potential future best practices for building modeling• Understand the value of a model for new and existing buildings• Introduce alternatives to ASHRAE 90.1
  3. 3. What’s a Model?
  4. 4. A MODEL is a device or structure that helps us:• Understand the world around us• Understand a piece of the world around us• A simplified representation of our surroundings in order that we may pursue understanding
  5. 5. Modeling Mindset “… we must pursue understanding. Not answers but understanding.” Bellinger G. (2004) “Simulation is not the Answer”
  6. 6. Modeling Mindset “Everything should be made as simple as possible, but not simpler.”
  7. 7. Modeling Mindset “Obstacles are those frightening things you see when you take your eyes off goals.” “Whether you think you can or think you can’t, you’re right.”
  8. 8. Building Modeling: BIM and BAMBIM: Building Information Model• Building Information• Uses include construction documents, clash detection & constructability, cost estimating, scheduling, etc.BAM: Building Analytical Model• Building Analysis• Uses include climate modeling, thermal loads modeling, structural loads modeling, daylight modeling, thermal comfort modeling, airflow modeling, temperature modeling, energy modeling, solar modeling, performance optimization, life cycle cost assesment, etc.
  9. 9. Building Analytical Modeling – Beyond Energy Daylight Model Airflow (CFD) Model Thermal Loads Model
  10. 10. BAM: Some more examplesSolar penetration Daylight levels Natural Ventilation Results color coded on model Daylight Metrics Climate Understanding J F M A M J J A S O N D Cop yright © 2008 Integrated Environmental So lutions Limited. All rights reservedMonthly Energy Output* Daylight contours Annual Energy Output*
  11. 11. Models for Buildings – Traditional PracticeMultiple Models for Multiple PurposesCAD/BIM for construction; HVAC loads, energy,daylight, solar, rendering, airflow, etc. Thermal Loads Solar Airflow (CFD) Energy Ventilation Daylight Rendering Artificial Light LEED Code Compliance
  12. 12. Traditional Practice - Benefits1. It’s “familiar” • Meaning Comfortable • “What we’ve always done” Traditional Practice - Drawbacks1. It’s “familiar” • Meaning Limited & Inefficient2. Lots (and lots) of repeated work • AKA - Inefficient3. Lots (and lots) of loopbacks4. Lack of Data Integrity • Accuracy and QA can easily suffer leading to higher chance for GIGO or incomparable results
  13. 13. Models for BuildingsPossible in Today’s Practice:Fewer Models serving Multiple Purposes:CAD/BIM for construction plus an AnalyticalModel studying thermal, energy, daylight, solar,airflow, comfort, etc. Building Analytical Model
  14. 14. Today’s Best Practice - Benefits1. It’s not familiar • Meaning innovative2. Less data entry • More time finding best solutions3. Fewer loopbacks • More efficient4. Lower chance for GIGO • Fewer datasets to manage and QC Today’s Best Practice - Drawbacks1. It’s not familiar • Meaning there is a learning curve • Innovation might be frightening to some • Initial investment period before efficiency is realized
  15. 15. Today’s Best Practice – Truly Informed Design Analysis Informs Design
  16. 16. Models for BuildingsIdeal Practice?: 1 Building, 1 Model
  17. 17. Ideal Practice? - Benefits1. Minimal re-work • Best efficiency2. Potential for minimal GIGO • More time finding best solutions3. Fewer loopbacks • More efficient4. Parametric • When one thing changes, other related items automatically updateIdeal Practice? - Drawbacks1. Karoshi2. Who manages what? • For example, is the architect now responsible for the quality of the thermal model? • GIGO potentially bigger problem if not caught early on and managed properly3. Too much detail – leads to instability and uncertainty in analysis4. Parametric – Is it now just a “black box”?
  18. 18. Measures of Quantity – BIM
  19. 19. Measures of Quantity – Project Delivery
  20. 20. Measures of Quality – Daylight Analysis
  21. 21. Understanding Visual Quality - Glazing Options Daylighting Quality Exterior TintSC = 0.6VLT = 75%SC = 0.2VLT = 35%
  22. 22. Understanding Quality - Glare & Solar Shades • Will glare be problematic late in the day? Lighting & Daylighting No Solar Shading • How Effective is the External (or Internal) Shade at reducing Glare? With Solar Shading
  23. 23. Understanding Solar Analysis Building self-shading Building self-shading through brise soleil Summer sun Winter sunUnexpected mid-evening peak Shading from adjacent buildings cooling load on east façade?
  24. 24. Understanding Quality of Envelope - Dynamic Infiltration Heating Load (Btu/h) Fabric Loss Infiltration Loss 0 2000 4000 6000 8000 10000 12000 14000 Infiltration heat loss can account for up to 40-50% of a building’s Heating Load.... ...Building Pressure Tests
  25. 25. Understanding Quality - Airflow (CFD)
  26. 26. Understanding Quality - Building Performance
  27. 27. Compliance With Codes & Rating Systems
  28. 28. BAM: Value to Existing Buildings• Predict energy use, costs during operation• Calibrate energy model per utility bills or building performance• Sensitivity Factors • Calibration methods, tools • Data collection • Utility rates
  29. 29. The Future: Smart Buildings• Continuous Calibration to Optimize Performance• Anticipate problems on the fly using trended data• Reduce Total Cost of Energy and Improve Occupant Comfort• Detailed Analysis Models will be the heart – Note: +/- 10% is NOT good enough – Note: “Fudging factors” will not work for Smart Buildings
  30. 30. Current Challenges• Cost of calibrated models• Construction QA practices lacking• Cheap Energy & Current Financial Metrics• Lack of accurate data• Lack of enough detailed data• “Fudge Factors” are still common practice• ASHRAE 90.1 Mindset
  31. 31. ASHRAE 90.1 – 2010• Prescriptive Path – Prescriptive Path encourages building the worst possible “legal” building; it does not encourage building the best possible building – There are no requirements for testing or QA during construction and occupancy• Performance Path (Appendix G “Baseline”) – There is no actual baseline in Appendix G – Appendix G does not allow for certain measures to be included • For example, reduction in OA by using a system type which delivers OA more efficiently – There are no requirements for testing or QA during construction and occupancy• Benchmark versus Goal – Benchmarks measure against current state; not against desired state – Goals identify desired state; current state is less important• Incredibly Complex – Creates confusion in the marketplace – Practitioners often spend more time on the baseline than on improving the proposed building• “Fudge Factors” are allowed – some even specified in Appendix G
  32. 32. ASHRAE 90.1 – 2010 New Appendix G requirements• Accounting for Site Conditions – Theory: Buildings aren’t built in a vacuum and site conditions do matter – Practice: Poor implementation of this theory leads to more confusion & inaccuracies • 90.1-2010 allows for site impacts that are physically impossible • 90.1-2010 has exceptions which allow some software modeling tools to easily fake results• Minimum requirements for HVAC efficiencies improved – Baselines are (theoretically) more efficient – Proposed case does not require modeling tools to accurately model actual HVAC systems • Convoluted (and frequently inaccurate) workarounds are still permitted• Envelope requirements require more insulation for certain climate zones – Meaning theoretical worst possible building is theoretically slightly better – Mass factors still allowed – meaning detailed accounting of thermal mass impacts is NOT REQUIRED• Incredibly Complex – 2010 version got more complex, not less – Practitioners often spend more time on the baseline than on improving the proposed building – this will probably get worse instead of better• “Fudge Factors” are allowed – some even specified in Appendix G
  33. 33. ASHRAE 90.1 – 2010 Detailed Solar for the Appendix G Baseline & Proposed Cases• Some obvious questions here: – If the simulation program cannot simulate shading by adjacent structures, how can it tell you which surfaces are shaded “most of the time”? Hence, how can you determine which surfaces should be modeled as north- facing? – What about urban areas? Rotation of baseline and proposed with site will cause physical impossibilities.
  34. 34. Self Shading Still not Required in 90.1 Building self-shading
  35. 35. Problems with Building Only Rotation
  36. 36. ASHRAE 90.1 – 20100-degree Solar for the Appendix G Baseline & Proposed Cases
  37. 37. ASHRAE 90.1 – 2010180-degree Solar for the Appendix G Baseline & Proposed Cases
  38. 38. Alternatives: Moving Beyond Benchmarks• A new paradigm: – Require design and construction teams build and design the best possible building – What is the best possible building? • Net Zero Energy • Wisconsin• New York • Hawaii
  39. 39. Net Zero Energy is the Index• Projects already constructed which achieve this standard• Penalizes waste and encourages best possible building• Simplifies the modeling process• Encourages teams to seek best possible solutions, not just minimums• More time available to explore best alternatives rather than spending excessive amounts of time struggling with theoretical baselines• Promotes understanding• Promotes changes to occupant behavior• Changes the financial model for implementing renewables• Grows several segments in the economy – Energy Modeling – Renewable Energy – Construction (renovation and new) – Generates a revenue source for new research • Funded by the biggest energy users• More efficient use of resources – Human – Renewable – Non-renewable

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