building energy simulation accuracy - u.s. doe energy efficiency
TRANSCRIPT
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NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.
Building Energy Simulation
Accuracy
Craig Christensen
Dave Roberts
Ben Polly
Marcus Bianchi
Neal Kruis
Ren Anderson
July 21, 2010
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Outline
• Background
• Predicted / Measured
• History / Context
• Modeling Issues
• Software Testing
• Gaps and Needs
• Future Work
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Background
• Preliminary Thinking
• A work in progress
• Your inputs desired
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Energy Prediction Accuracy for Existing Homes:
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Predicted / Measured
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Predicted / Measured
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Old Buildings New Buildings
Predicted / Measured
House-by-house:
- Operational ratings
- Utility-bill calibration
Asset ratings
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Actual
Use
Predicted
Use
Asset Rating
• building models
• building characteristics inputs
• standard operational assumptions built-in
a
Predicted / Measured
oOperational Rating
• building models
• building characteristics inputs
• occupant-specific operational inputs
a
o
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Actual
Use
Predicted
Use
Reduced variance
Predicted / Measured
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Actual
Use
Predicted
Use
o
ac
Utility-bill calibration
• adjusts building/operational characteristics
so that predicted use matches actual use
• applied on a house-by-house basis
• not exact for end uses or measure savings
(initial building model should be accurate)
a
oc
Predicted / Measured
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Actual
Use
Predicted
Use
Asset Ratings
Predicted / Measured
Errors / Inadequacies:
1) building models
2) building characteristics inputs
3) standard operational assumptions
Bias
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If pre-retrofit energy use is over-predicted …
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Predicted / Measured
(Energy Use)Before
… then there is the possibility (likelihood)
that savings will be over-predicted.
- (Energy Use)After---------------------------------------------------------------------------------
Energy Savings
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Predicted/Measured
Realization rates include effects of operational changes with retrofit (e.g., take-back).
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History / Context
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History/Context
Question: How can energy prediction tools that have been
developed over many years be significantly wrong?
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Answer: Existing-home energy analysis is a niche application
Building energy calculations (and research)
have historically been focused on:
1) Equipment sizing
2) Commercial buildings
3) New buildings
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Sizing Calculations
• Conservative “worst case“
assumptions
Energy Predictions
• Representative “typical”
assumptions
History/Context
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Commercial Buildings
• Simple geometry
• Limited shading
• Limited wind shielding
• Multiple conditioned zones
Residential Buildings
• Articulated geometry
• Increased shading
• Increased wind shielding
• Multiple buffer zones
(garage, attic, crawl space)
History/Context
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Inside Outside
R-0.68 R-0.19
Rgap = 3.13
History/Context
New Buildings
Low-E
Increased sensitivity
to boundary conditions
Old Buildings
Inside Outside
R-0.68 R-0.19
Rglass = 0.03
Single-glazed
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Modeling Issues
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User Inputs
Analysis Tool(BEopt, HESpro)
Models:
• algorithm
• coefficients
Internal Inputs:
• defaults
• calculated
• built-in
• models, modes
Simulation Engine(DOE-2, EnergyPlus)
Modeling Issues
Errors / Inadequacies:
1) building models
2) building characteristics inputs
3) standard operational assumptions
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Modeling Issues
•Exterior: infrared
•landscaping, neighbors
•insect screens
•Exterior: convection
•landscaping, neighbors
•insect screens
•Interior: infrared
•partition walls
•blinds, drapes
•Interior: convection
•blinds, drapes
•Solar gains
•landscaping, neighbors
•Insect screens
•blinds, drapes
•Infiltration
•landscaping, neighbors
•conduction heat recovery
•Unfilled-cavity R-values
•Infiltration
•Thermal mass
• non-structural
•Thermostat Setpoints
•before retrofit
•after retrofit
•Zoning
•Interior temperatures
•solar gain
•Internal gains
•Interior Temperature
•stratification
•Insulation R-value
•temperature-dependence
•HVAC size
•under-sized before retrofit
•over-sized after retrofit
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Interior Radiation:
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Tin
Ts,in
conv
rad
DOE-2
Ti
n
Ts,in Twall
rad
EnergyPlus
Modeling Issues
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Software Testing
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Software Testing
Software-to-Software Comparisons:
• BESTEST_EX
• BEopt Test Suite
Objectives:• Validation
• Diagnostics
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BESTEST- EX: “Building Physics” Case
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BESTEST- EX: “Utility Bill Calibration” Cases
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BEopt input
New Construction: ~400 options (in ~50 categories)
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BEopt Test Suite
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Minimal Tests
Simulation Differences (DOE-2 versus EnergyPlus) Atlanta, GA
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BEopt Test Suite
National Renewable Energy Laboratory Innovation for Our Energy Future
Minimal Tests
Simulation Differences (DOE-2 versus EnergyPlus) Phoenix, AZ
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BEopt Test Suite
National Renewable Energy Laboratory Innovation for Our Energy Future
Minimal Tests
Simulation Differences (DOE-2 versus EnergyPlus) Chicago, IL
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BEopt Test Suite
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BEopt Test Suite
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BEopt Test Suite
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BEopt Test Suite
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BEopt Test Suite
National Renewable Energy Laboratory Innovation for Our Energy Future
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BEopt Test Suite
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BEopt Test Suite
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Gaps and Needs
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Gaps and Needs
Gaps:
• Current tools do not reliably predict:
pre-retrofit energy use
retrofit energy savings
Needs:
• Identification of potential sources of discrepancies
• Investigation / resolution of modeling issues
• Validation of improved inputs/models against field data
• Development of analysis best practices
• Updated standard test procedures
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Future Work
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Residential Energy Simulation --Test and Improvement Process
Sensitivity
Testing
Literature
Review
Define
Question
Technical
Approach
Develop
Solution
Test:
• Empirical
• Numerical
Identify Modeling Issues:
• Models/Coefficients
• Asset Inputs
• Operational Inputs
Prioritize:
• Discrepancy size
• Level of effort
Recommended
Best Practice
Updated Test
Procedures:
• ASHRAE 140
Aggregate Solution
Testing:
• Software-to-Empirical
• Software-to-Software
Advisory
Experts
NREL
Working Group