Transcript Joshua New, Ph.D. Oak Ridge National Laboratory [email protected] 865-241-8783 Technical Paper Session 3 Evolutionary Tuning of Building Models to Monthly Electrical Consumption Building Energy Modeling and Calculations.

Joshua New, Ph.D.
Oak Ridge National Laboratory
[email protected]
865-241-8783
Technical Paper Session 3 Evolutionary Tuning of
Building Models to Monthly
Electrical Consumption
Building Energy Modeling and Calculations
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Learning Objectives
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Describe reasons for and challenges involved with creation of an
automated calibration methodology
Explain how evolutionary computation works and how effectively it can
create calibrated models
Provide an overview of the EnergyPlus VRF Heat Pump Computer
model
Demonstrate the VRF computer model verification using manufacturer’s
data
Distinguish between five different existing methods for calculating
distribution of absorbed direct and diffuse solar gains in perimeter
building zones
Understand the impact of solar energy distribution on heating and
cooling loads as well as on free-floating room air temperatures for
various climates and building envelope options
ASHRAE is a Registered Provider with The American Institute of Architects Continuing Education Systems. Credit earned on
completion of this program will be reported to ASHRAE Records for AIA members. Certificates of Completion for non-AIA
members are available on request.
This program is registered with the AIA/ASHRAE for continuing professional education. As such, it does not include content
that may be deemed or construed to be an approval or endorsement by the AIA of any material of construction or any
method or manner of handling, using, distributing, or dealing in any material or product. Questions related to specific
materials, methods, and services will be addressed at the conclusion of this presentation.
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Acknowledgements
• Thanks go to:
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Aaron Garrett, Ph.D. – Jacksonville State University
Theodore Chandler – Jacksonville State University
Amir Roth – DOE Building Technologies Office
Oak Ridge Leadership Computing Facility
Remote Data Analysis and Visualization Center
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Objectives Q&A
• What are two of ASHRAE’s primary sources for
calibration, what is their purpose, and what
performance metrics do they use?
• What does SAE mean and what is its strength as a
performance metric?
• What is one of the acceleration methodologies used
to speed up the calibration process and is it
justifiable?
• How well does envelope-only automated calibration
currently do compared to human calibration?
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Outline/Agenda
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Context and calibration guidelines
Evolutionary computation (EC) overview
EC-based Autotune for building calibration
Acceleration method
Autotune calibration results
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Context and Calibration Guidelines
• Tool using BEM: retrofit optimization
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Context and Calibration Guidelines
• “All (building energy) models are wrong, but some are useful”
– 22%-97% different from utility data for 3,349 buildings
• More accurate models are more useful
– Error from inputs and algorithms for practical reasons
– Useful for cost-effective energy efficiency (EE) at speed and scale
• Calibration is required to be (legally) useful
– ASHRAE G14 (NMBE<5/10% and CV(RMSE)<15/30% monthly/hourly)
• Manual calibration is risk/cost-prohibitive
– Development costs 10-45% of federal ESPC projects <$1M
– 114 of 119 US buildings are residential, 9% of ESCO market
• Need robust and scalable automated calibration for market
– Adjusts parameters in a physically realistic manner
– Scales to any available data and model (audit)
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Autotune
E+ Input
Model
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EC Overview
• Evolutionary computation simulates
natural selection
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Genetic algorithms
Evolution strategies
Genetic programs
Particle swarm optimization
Ant colony optimization
• EC approach to building calibration
– Individual – a building (list of input parameters)
– Fitness – error between simulation output and sensor data
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EC Autotune
What is an individual?
• Defined by 108 real-valued parameters
– Material
• Thickness
• Conductivity
• Density
• Specific Heat
• Thermal Absorptance
• Solar Absorptance
• Visible Absorptance
– WindowMaterial:SimpleGlazingSystem
• U-Factor
• Solar Heat
– ZoneInfiltration:FlowCoefficient
– Shadow Calculation Frequency
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EC Autotune
What is the fitness?
Individual
Fitness
Model
Error
Actual Building Data
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EC Autotune
How do they evolve?
Sister
Mom
Brother
Dad
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EC Autotune
How are offspring produced?
Thickness
Conductivity
Density
Specific Heat
Mom
0.022
0.031
29.2
1647.3
Dad
0.027
0.025
34.3
1402.5
Brother
0.0229
0.029
34.13
1494.7
Sister
0.0262
0.024
26.72
1502.9
• Average each component
• Add Gaussian noise
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EC Autotune
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Population size 16
Tournament selection (tournament size 4)
Generational replacement with weak elitism (1 elite)
Gaussian mutation (mutation rate 10% of variable range)
Heuristic crossover
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Acceleration Method
• Pick 1024 sub-atomic particles from the universe
• EnergyPlus is slow
– Full-year schedule
– 2 minutes per simulation
• Use abbreviated 4-day schedule instead
– Jan 1, Apr 1, Aug 1, Nov 1
– 10 – 20 seconds per simulation
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Acceleration Method
• 4 independent random trials
• 1024 simulations per trial
• Samples taken from high to low error
r = 0.94
Monthly Electrical Usage
r = 0.96
Hourly Electrical Usage
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Acceleration Method
Individual
Fitness
Model
Error
Actual Building Data
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Acceleration Method
Combining serially…
Evolve
Evolve
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Acceleration Method
Combining in parallel…
Island
Hopping
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Autotune Calibration Results
25% reduction in error in 10 generations typical
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Autotune Calibration Results
What are you comparing to?
Model
Monthly SAE
Hourly SAE (kWh)
Hourly RMSE
V7-A2
1276.340
6242.036
1.20594
28July2010
1623.364
8113.685
1.62455
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8030
𝑆𝐴𝐸 =
𝑀𝑖 − 𝐴𝑖
𝑀𝑖 − 𝐴𝑖
𝑖=1
1800
1,623.4
9000
8,113.7
8000
7000
1,276.3
RMSE =
1.8
1.4
6,242.0
6000
1.2
1000
5000
1.0
800
4000
0.8
600
3000
0.6
400
2000
0.4
200
1000
0.2
0
0
28July2010
Monthly SAE
2
1.6
1.6
1200
V7-A2
𝑀𝑖 − 𝐴𝑖
8030
𝑖=1
1600
1400
8030
𝑖=1
1.2
0.0
V7-A2
28July2010
Hourly SAE
V7-A2
28July2010
Hourly RMSE
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Autotune Calibration Results
How well did Autotune do?
• Autotune 108 envelope parameters 60% toward best manual model
• Autotuned best model within $9.46/month (actual use $152/month)
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Bibliography
• ASHRAE. 2013. Evolutionary Tuning of Building Models
to Monthly Electrical Consumption. ASHRAE
Transactions 119(1) (pending publication)
• 22 Autotune-related publications:
– 1 PhD dissertation, 9 accepted publications, 6
submitted publications, and 6 internal reports
– Download data, view tuning dashboards, etc.
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Questions?
Joshua New
[email protected]
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