delivering energy efficient buildings: applications …...increasing integration of subsystems &...
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Dr. Satish Narayanan 860.610.7412
Satish.Narayanan@utc.com
Delivering Energy Efficient Buildings:
Applications and Opportunities for Advances
in Computations, Dynamics & Controls
Minneapolis, MN
June 11, 2013
IMA Hot Topics Workshop
Mathematical and Computational Challenges in the Control,
Optimization, and Design of Energy-Efficient Buildings
No technical data subject to the EAR or ITAR
2
Key Points
• Substantial energy use reductions in built infrastructure can be realized
using a systems approach (70-80% reductions possible)
• Buildings are complex systems typified by uncertainty and dynamics over a
large range of scales
• Industry has different needs for computation and controls • Multi-physics, multi-scale (~O(10
6) range) dynamics encountered
• Optimize design choices (100’s-1000’s of components, controls, sensors…)
subject to uncertainty
• Algorithms and tools to automate synthesis, verification and commissioning of
robust controls and diagnostics solutions
• On-line estimation, optimization, data assimilation techniques for operations
• Transformative impact achievable by directing advances to create algorithms
and toolboxes that can be used by industry • Productivity: Reduce design cycle time from months → days/weeks
• Quality: Reduce performance uncertainty from >30% → <5%
• Cost: Cut commissioning and O&M costs by 2-5x (reduce from months → days)
No technical data subject to the EAR or ITAR
Why Should We Care?
3
39% → of total US energy
71% → of US electricity
54% → of US natural gas
48% → US Carbon emissions
$120B → Commercial building annual
energy bill
17% → growth in energy intensity
(1985-2000)
1.7% → annual growth projected
through 2025
Sources: Ryan & Nicholls 2004, USGBC, USDOE 2004
No technical data subject to the EAR or ITAR
4
Outline
• Achievable gains in building energy efficiency
• Barriers to realizing energy efficiency gains and industry issues
• Underlying mathematics, modeling and computation issues
• Examples of progress in methods, tools and technologies
• Summary remarks
No technical data subject to the EAR or ITAR
Highly Energy Efficient Buildings Exist
5
Mar
ket P
enet
ratio
n/S
ize
and
Rea
dine
ss
Energy Efficiency 10-20%
“Climate Adaptive Design”
20-40% 50%+
“One size fits all”
KfW Frankfurt, Germany
55K ft2, 100kWhr/m2
Increasing integration of subsystems & control
Different types of equipment
Different skills
Different delivery models
Debitel Stuttgart, Germany
120K ft2, 165kWhr/m2/yr
No technical data subject to the EAR or ITAR
0
100
200
300
400
500
600
700
US Average JapanAverage
GermanyAverage
WestEnd Duo Debitel DeutschePost
DS-Plan
Pri
mary
En
erg
y I
nte
nsit
y (
kW
hr/
m2) Internal Loads
Internal Loads (est)
HVAC + Lighting(breakout not available)
Lighting
Ventilation
Space Cooling
Space Heating
Commercial Office Building Energy Use
Est.
Est.
6 No technical data subject to the EAR or ITAR
High Performance Buildings: Case Studies
• Visits to building sites and design companies in Germany and Switzerland
conducted July (2009) to understand the design and delivery of low energy buildings
• The buildings typically targeted energy intensity of 100 kWh/m2/year (excludes plug
loads); less than half of typical German energy usage and a third of those in U.S.
• Most buildings have sustained, measured low energy performance
KfW Westar-
cade KfW Ostarcade DFS Westend Duo Debitel Theater Haus Mercedes DS-Plan Euweg
Frankfurt
Germany
Frankfurt
Germany
Frankfurt
Germany
Frankfurt
Germany
Stuttgart
Germany
Stuttgart
Germany
Stuttgart
Germany
Stuttgart
Germany Zurich, Switzerland
Bank campus fo-
cused on low
energy. Under
construction
Bank campus
focused on low
energy.
National flight
training school.
Owner occupied
office complex.
Green office build-
ing. Sustainability
with tenant flexibili-
ty.
Tower developed
for owner occupan-
cy. Now tenant
occupied.
Low budget re-use
of space for theater
complex. Willing
to compromise
comfort for cost.
Premium space that
while using low
energy techniques is
focused entirely on
comfort and style.
A small low ener-
gy office building.
A low energy office
building.
7 No technical data subject to the EAR or ITAR
Climate Adaptive Buildings: Design of Dynamics
Current State: One-size-fits-all
Lighting and solar
gain cooled by HVAC
Ignore local climate:
RTU/VAV/Chillers cooling,
forced air ventilation
Low E Buildings: Robust, Engineered Systems
Decouple lighting
and solar gain
from HVAC
Decouple sensible
heating/cooling from ventilation
Leverage local
climate: geothermal,
natural ventilation
8 No technical data subject to the EAR or ITAR
9
Outline
• Achievable gains in building energy efficiency
• Barriers to realizing energy efficiency gains and industry issues
• Underlying mathematics, modeling and computation issues
• Examples of progress in methods, tools and technologies
• Summary remarks
No technical data subject to the EAR or ITAR
Energy Efficient Building Design: Reality
Designs over-predict gains by ~20-30%
Large Variability in Delivered Performance
Performance simulations conducted (only) for peak conditions
As-built specifications differ from design intent, compromising energy performance, due to detrimental sub-system interactions
Building control systems not installed, commissioned or operated well
Uncertainty in operating environment and loads
M. Frankel (ACEEE, 2008)
10 No technical data subject to the EAR or ITAR
Energy Efficient Building Operation: Reality
Year 1 Year 2 Year 3
KfW East Arcade Building
Case Study
Primary Site Energy
Various Loads
Tuning the controls for night purge
(pre-cooling thermal mass)
11 No technical data subject to the EAR or ITAR
Monitoring and Tuning Necessary to
Achieve Energy Performance Targets
12
Property Managers &
Operations Staff
Operations & Maintenance Concept & Design
Contractors, OEM’s
Build
A & E Firms
Systems Not Robust Benefits Do Not Persist Design Not
Scalable
Delivering Energy Efficient Buildings: Industry Drivers
EEB’s can take up to 12 mos.
to design & optimize
Delivered system
performance vary by >30%
>20% energy wasted in operations
70% cost of controls incurred in
commissioning
$100’sK spent for each building! Huge “untapped” margins in
delivered performance
5-10% of facility operating cost
Up to 30% spend on O&M cost Implication
LBNL report
Issue
No technical data subject to the EAR or ITAR
13
Outline
• Achievable gains in building energy efficiency
• Barriers to realizing energy efficiency gains and industry issues
• Underlying mathematics, modeling and computation issues
• Examples of progress in methods, tools and technologies
• Summary remarks
No technical data subject to the EAR or ITAR
14
• Components do not have mathematically similar structures and involve different
scales in time or space;
• The number of components are large
• Components are connected in several ways, often nonlinearly and/or via a network.
Local and system wide phenomena depend on each other in complicated ways
• Overall system behavior can be difficult to predict from behavior of individual
components. Overall system behavior may evolve qualitatively differently, displaying
great sensitivity to small perturbations at any stage
* APPLIED MATHEMATICS AT THE U.S. DEPARTMENT OF ENERGY: Past, Present and a View to the Future
David L. Brown, John Bell, Donald Estep, William Gropp, Bruce Hendrickson, Sallie Keller-McNulty, David Keyes,
J. Tinsley Oden and Linda Petzold, DOE Report, LLNL-TR-401536, May 2008.
Going from 30% efficiency to 70-80% efficiency
Complexity* in Building Systems
No technical data subject to the EAR or ITAR
15
Computations for Building Scale Problems
Isolated Thermal
Environment in an
Individual Zone/Room
Multi-zone Building Simulation
(simplified geometry and
boundary conditions)
Whole Building Simulations
(complex geometry, multiple
sub-systems, and realistic
indoor/external uncertainties)
from UTRC/VT
from Transolar Engineering
from LBNL
10 TFlops → 10 Pflops Computation Capability*
* Assuming less than 1hour turnaround for
practical design calculations (J. Borgaard, VT) No technical data subject to the EAR or ITAR
16
Modeling: Heterogeneity
Equipment & distribution models
Building structure and indoor thermal models Building airflow models
Simple Representation of Building System
No technical data subject to the EAR or ITAR
Uncertainty Propagation: Large Parameter Space
17
• Disturbances in operating environment
defeat conceptually sound low energy
design principles
• Models of dynamics critical for
estimation and control
• Few parameters and interfaces can
dramatically impact energy performance
• Analysis computationally intractable
for large no. of parameters
• Must identify critical parameters
from Mezić, Eisenhower/AimDyn
from Aaborg U.
No technical data subject to the EAR or ITAR
Controls: Performance vs Optimality
18
Coordinated & Predictive Controls
Temperature control
Slab: MPC given 18 hour / degree time constant
Local fine-tuning: local heat/AC add & operable windows
Ventilation
Night purge: daily event
Buoyancy modes: tight envelope and flow
Heat and Cooling Sources
Geothermal: circulating mode, heat pump mode, AC mode
Solar gain: outdoor shading
Lighting
Daylighting: diffuse light shelves
Stronger Coupling
Performance Fragility Intrinsically Robust
Performance
Nested Loop Controls
No technical data subject to the EAR or ITAR
19
Outline
• Achievable gains in building energy efficiency
• Barriers to realizing energy efficiency gains and industry issues
• Underlying mathematics, modeling and computation issues
• Examples of progress in methods, tools and technologies
• Summary remarks
No technical data subject to the EAR or ITAR
20
Uncertainty Analysis and Quantification
Collaboration: SERDP/DoD, AimDyn
Ref: SERDP EW-1709 Final Report (2012)
Building 1225
Ft. Carson, CO
1000’s 10’s
No technical data subject to the EAR or ITAR
21
Model-based Control Design
Collaboration: SERDP/DoD, Virginia Tech
Ref: SERDP EW-1709 Final Report (2012)
Navy Drill Hall
Great Lakes, IL
No technical data subject to the EAR or ITAR
22
On-Line Dynamic Optimization
70
70.5
71
71.5
72
72.5
73
73.5
74
Av
era
ge
In
do
or
T_
SP
(oF
)
Test#1 Test#2 Test#3 Test#4 Test#5
DDCMPC
400
500
600
700
800
900
1000
1100
Test#1 Test#2 Test#3 Test#4 Test#5
DDCMPC
Max
imu
m In
do
or
CO
2Le
vel (
pp
m)
Upper Limit on Indoor CO2 Levels
Energy
savings
Zone
temperature
variation
Army CERL/ERDC
Champaign, IL
No technical data subject to the EAR or ITAR
Collaboration: ESTCP/DoD, UC Berkeley
Ref: ESTCP EW-0938 Final Report (2012)
23
Outline
• Achievable gains in building energy efficiency
• Barriers to realizing energy efficiency gains and industry issues
• Underlying mathematics, modeling and computation issues
• Examples of progress in methods, tools and technologies
• Summary remarks
No technical data subject to the EAR or ITAR
24
Summary Remarks
No technical data subject to the EAR or ITAR
Building energy efficiency matters and substantial gains at affordable cost
(even net zero energy buildings) possible
Buildings as complex systems present a rich portfolio of investable areas for
computational and mathematics advances
Design
− reduced-order dynamic models amenable to optimization and control design
− scalable computational techniques to quantify uncertainty and sensitivity
− techniques for model reduction and control analysis with whole building models
Operation
− robust and scalable computational techniques for on-line implementation of
adaptive, predictive, and optimal control schemes
− data assimilation techniques for system to component fault isolation, diagnoses
− validation and verification techniques for software-/hardware-in-the-loop
capability for whole building control and diagnostic systems
Background Material
25 No technical data subject to the EAR or ITAR
26
Acknowledgements
Sunil Ahuja, Sorin Bengea, Francesco Borrelli, John Burns, Eugene Cliff, Paul Ehrlich,
Bryan Eisenhower, John Grosh, Michael Holtz, Anthony Kelman, Clas Jacobson,
Helmut Meyer, Igor Mezic, Zheng O’Neill, Kevin Otto, Amit Surana, Michael Wetter
No technical data subject to the EAR or ITAR
27
Back Up
Vision
We need to do more transformational research at DOE … including computer design
tools for commercial and residential buildings that enable reductions in energy consumption
of up to 80 percent with investments that will pay for themselves in less than 10 years
Dr. Steven Chu, House Science Committee Testimony, March 17, 2009
We will nurture a system integration approach to building design, aided by computer
tools with embedded energy analysis. It was the system integration of the automobile
engine, transmission, brakes and battery that enabled Toyota to create the Prius. With
computer control of ignition timing and fuel mix, today’s automobile engines operate at 20
percent higher efficiency. With computer monitoring and continuous, real-time control of
HVAC systems, lighting, and shading, far more spectacular efficiencies can be realized in
buildings. There is a growing realization that we should be able to build buildings that will
decrease energy use by 80 percent with investments that will pay for themselves in less than
15 years. Buildings consume 40 percent of the energy in the U.S., so that energy efficient
buildings can decrease our carbon emissions by one third.
Secretary Chu, Caltech Commencement, June 12, 2009
28 No technical data subject to the EAR or ITAR
Market and Regulatory Landscape Changing Rapidly Whole Building Energy Performance Ratings
29 No technical data subject to the EAR or ITAR
30
Industry Needs Tools That Improve Decision Making
Select system
architectures
System & component
performance analysis and
design/specification
Control & software definition
Robustness & risk assessment
System verification
testing, installation
& commissioning
Performance monitoring,
optimization,
diagnoses
Building
Lifecycle
Plan Build Operate Design
Toolboxes for control
design & validation
Uncertainty/risk
management tools
Tools for
optimization
No technical data subject to the EAR or ITAR
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