delivering energy efficient buildings: applications …...increasing integration of subsystems &...

Dr. Satish Narayanan 860.610.7412

[email protected]

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)


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


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


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


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.


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


9

Outline





• Summary remarks


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)


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)


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


13

Outline





• Summary remarks


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


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


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.


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


19

Outline





• Summary remarks


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


21

Model-based Control Design

Collaboration: SERDP/DoD, Virginia Tech

Ref: SERDP EW-1709 Final Report (2012)

Navy Drill Hall

Great Lakes, IL


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


Collaboration: ESTCP/DoD, UC Berkeley

Ref: ESTCP EW-0938 Final Report (2012)

23

Outline





• Summary remarks


24

Summary Remarks


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


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


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


Market and Regulatory Landscape Changing Rapidly Whole Building Energy Performance Ratings


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


delivering energy efficient buildings: applications …...increasing integration of subsystems &...

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