Lawrence Berkeley National Laboratory
Energy Efficiency Perspectives:
Intelligent Networks andThe Challenge of
Zero Energy BuildingsStephen Selkowitz
Department Head, Building Technologies DepartmentLawrence Berkeley National Laboratory
[email protected]/486-5064
Connected Urban DevelopmentGlobal Conference 2008
Connected and Sustainable Energy
Defining the Energy/Climate Change Problem:Defining the Energy/Climate Change Problem:5 Supply Perspectives and 1 Demand5 Supply Perspectives and 1 Demand
Energy Efficiency in Buildings
Nuclear
Biofuels
Wind power
Solar powerCarbon Storage
Lawrence Berkeley National Laboratory
U.S. End-Use Energy Split
Building Energy Use:
39% total U.S. energy40% of carbon emissions71% electricity54% of natural gas
Fastest growth rate!
Lawrence Berkeley National Laboratory
39% total U.S. energy71% electricity, 54% of natural gas
Building Energy Use
No “silver bullet” solutions: heating, cooling and lighting dominate but mustaddress complexity of end use splits, which vary by sector and climate
Lawrence Berkeley National Laboratory
National Lighting Energy Consumption
Source: Navigant Consulting, Inc., U.S. Lighting Market Characterization, Volume I: National Lighting Inventory and, Energy ConsumptionEstimate, Final Report for US DOE, 2002
Lighting Energy Consumption by MajorLighting Energy Consumption by MajorSector and Light Source TypeSector and Light Source Type
Breakdown of Lighting EnergyBreakdown of Lighting Energy
Incandescent40%
Fluorescent38%
HID22%
LED (<.1%)
390 Billion kWh used for lighting in all390 Billion kWh used for lighting in allcommercial buildings in 2001commercial buildings in 2001
Commercial Building Lighting wastes energy becausedimming lighting controls are not widely used
Vacancy Detection or SchedulingAutomatic Dimming with DaylightTuning Strategies
Personal dimming controlsInstitutional requirements
Lumen MaintenanceDemand Response
All Lighting Should be:All Lighting Should be:•• DimmableDimmable•• AddressableAddressable•• (Affordable)(Affordable)
Major Lighting ControlMajor Lighting ControlStrategiesStrategies
Lawrence Berkeley National Laboratory
Good Lighting Controls (Daylight Dimming) Work
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Day of Year 1990
kWh/12 hr/zoneDaily Energy Use (6 A.M to 6 P.M.)
Data fromadvancedlighting controlsdemonstrationin Emeryville, CA(1990) !!!
Energy Usebefore retrofit:
After retrofit:South zone:North zone:
40-60%Savings
40-80%Savings
Lawrence Berkeley National Laboratory
Mesh Networks: WirelessLighting Controls:
Single Chip Mote FeasibilityDemonstrated
Single Chip mounted to a boardfor integration with lighting
components
Wireless Control by single-chip mote demonstrated in
ACM & Ballast
Making Lighting Controls Intelligent:Adding Wireless Communications Capabilities to Ballasts
Lawrence Berkeley National Laboratory
Potential Impacts of Advanced LightingControls in California Buildings
Lawrence Berkeley National Laboratory
The New York TimesHQ Building
Owners program:• 52 floors, 160,000 sq.M• Highly glazed façade gives workers views and allows
the city to see “news” at work• But glare, cooling, visibility etc
Need/Goal:• Develop integrated , automated shading and
dimmable lighting system– Affordable, reliable and robust
• Transform the market- push these solutions towardwidespread use
Challenge:• How to develop a workable integrated
hardware/software solution• How to “guarantee” that such a solution will work in
practice
Lawrence Berkeley National Laboratory
12Approach: Test Performance of Systems
Options in a Full-Scale Mockup of part of a floor
•Evaluate Shading,daylighting, employeefeedback and constructabilityin a ~4500 sf testbed
•Fully instrumented; 1 yeartesting
•Concerns with glass facade:– Window glare (Tv=0.75)– Control of solar gain/cooling– Daylight harvesting
potential•Lighting Systems
– Daylight dimming– Addressable systems– Task tuning– Load Shed/DR
•Real sun and sky conditions,12-month monitored period
North
A
B
Lawrence Berkeley National Laboratory
13Extend Testbed Results to All Floors and
Orientations using Simulation ToolsDevelop Shade Control Algorithms for Motorized Shades
using Simulation Results
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Simulated Views from 3 of22 view positions
• Each shade system has its own sensor and motors• Performance will vary with orientation, floor elevation,
view out, and neighboring buildings.• How to address performance with this variance?• Build a virtual model of the building in its urban
context using hourly weather data simulateperformance
3-D Digital model of site
Lawrence Berkeley National Laboratory
Challenge: Verifying Installation and Field PerformanceNew Tool used by owner to check calibration of installed systems
• High-dynamic range (HDR) digital images• Captured automatically, processed within 1 minute,
then produces continuous luminance maps of thescene.
– Accuracy to +/- 10% within 0-5000 cd/m2 range• R&D tool developed in testbed
• Verifies that installation meets specs• “Production tool” used by owner in building ----------->
• Dimmable lighting• Addressable• (Affordable)(1/3 original cost estimate)
• (Multifunctional)
Intelligent Lighting and Shade ControlIntelligent Lighting and Shade Control -- now in NYC!now in NYC!
New York Times office with dimmablelights and automated shading
Occupied 2007
Lawrence Berkeley National Laboratory
Controls for Natural Ventilation:San Francisco Federal Building
•Natural ventilation in tower – no mechanical cooling or ventilation in open-plan
perimeter office space
•Mechanically operated and manually operated windows
•Extensive daylighting, dimmable lighting
•Designed with state-of-the-artsimulation tools, EnergyPlus*and CFD
•Control system tested withEnergyPlus prior to installation
•Virtual Controls Testbed - tooptimize the strategies foropening windows for cooling
© André Anders & Windows Group (EETD), 2007
Energy/Demand Management with ActiveEnergy/Demand Management with ActiveFaFaççades+ Daylighting Controlsades+ Daylighting Controls
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Lighting
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Typical commercialbuilding load profile
Peak demand reductionsduring curtailments
Lighting: 75%Air conditioning: 25%Other: 10%
A/C
Other
DimmedLighting
ReducedSolar Gain
ElectricDemand
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Automated Demand ResponseDR Definition: Action to reduce load when
• Contingencies occur that threaten supply-demand balance
• Market conditions occur that raise supply costs– peak-load reductions different from efficiency, transient vs. permanent
DR Communications Infrastructure Needs• Create real-time, automated DR infrastructure to respond to changing contingency and market
conditions• DR infrastructure should coexist with legacy systems, technology and tariff improvements, with near-
and long-term benefits.
C a l i f o r n i a D a i l y P e a k L o a d s - - 2 0 0 6
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R e s i d e n t i a l A i r C o n d i t i o n i n g
C o m m e r c i a l A i r C o n d i t i o n i n g
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DRAS Clients –
1. Software only (Smart)
2. Software & Hardware(Simple)
DR Automation Server and Client
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Auto-DR in 130,000 ft2 County OfficeCurrent Practice
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Time Scales of Building/Grid Optimization –Automated DR Future
Time of Use Optimized
Recent Energy Efficiency Activity
•“Greening the Capitol” Project– Make the House buildings Carbon Neutral
in 10 years– Plan published; Action launched
•Architecture 2030 - Zero EnergyBuildings– AIA and 500 cities have signed on
•California PUC: Launches “BigBold” initiatives– ~$1B/yr on Efficiency; shift to longer term
focus– “New Commercial Buildings are Zero Net
Energy by 2030”
Vision: Zero Energy BuildingCreating a New Generation of Net-Zero Energy, Carbon-Neutral Buildings
Automation• Energy sensors & actuators• Wireless communication• Feedback control systems
Cool Stuff
Tunable WindowsFunctional BuildingMaterials• Thermal• Structural
Getting toGetting to ““Zero Net EnergyZero Net Energy”” oror ““CarbonCarbonNeutralNeutral”” BuildingsBuildings
• Deployment: (5 - 30% savings)— Identify what works and deploy it widely— Applies to all buildings: new and existing— Mandatory programs: codes and standards— Voluntary programs: incentives— e.g. Clinton Climate Initiative
• Demonstrate Emerging Solutions (20 - 60% savings)— Find Underutilized, unproven technologies and systems— R&D to improve, optimize; Make them mainstream— e.g. New York Times
• Breakthrough Innovations (50-80% savings plus on-siterenewable power)— New, more effective, high performance options— Lower costs, Lower risk
Lawrence Berkeley National Laboratory
What Will it Take to Achieve 2030 Targets?
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Existing Buildings Retrofit Buildings New Buildings
New Commercial Buildings Save 90% by 2030plus 50% Retrofit Savings by 2030
These levels ofefficiency are unlikely tobe achieved by marketforces alone;
Major new public/privateinitiatives to drivetoward goals
Business opportunitiesfor firms with“solutions”
BAU
page 28
““Think Big, Start Small, Act NowThink Big, Start Small, Act Now””
• Challenge of launching and sustaining a large scale,long term, national program, blending policy, economicsand technology
• Public - Private partnership• New and Existing Commercial Buildings
• Long Term effort - 10-20 years
• “You cant manage what you don’t measure…”• Making Performance “Visible” - display energy use
• IT network and smart controls enable real time, high resolution,performance monitoring from devices to buildings to grid
• Get involved………
• Zero Energy Commercial Building Initiative• www.zeroenergycbi.org