Advanced Controls and Communication Systems for
Demand Response and Energy Efficiency
in Commercial Buildings
Sila Kiliccote, Mary Ann Piette
Lawrence Berkeley National Laboratory
SKiliccote@lbl.gov, MAPiette@lbl.gov
David Hansen
U.S. Department of Energy
January 12, 2006
Second Carnegie Mellon Conference in Electric Power Systems:
Monitoring, Sensing, Software and Its Valuation for the Changing Electric
Power Industry
Sponsored by U.S. DOE, California Energy Commission and
New York State Energy Research and Development Authority
1
Presentation Overview
• Demand Response Basics and DR in US
• Demand Response Potential in Commercial
Buildings
• Advanced Controls for Commercial
Buildings
• Research in California
• Automation of DR
• Research in New York
• New York Times Office Building
• National R&D Opportunities
2
Demand Response Definition
• Demand Response (DR) is the action taken to
reduce load when:
• Contingencies (emergencies & congestion)
occur that threaten supply-demand balance,
and/or
• Market conditions occur that raise supply
costs
• DR typically involves peak-load reductions
• DR strategies are different from energy
efficiency, i.e., transient vs. permanent
3
Demand Side Management
Efficiency and
Conservation
(Daily)
Peak Load
Management
(Daily)
Demand
Response
(Dynamic
Event Driven)
Motivation
- Environmental
Protection
- Utility Bill
savings
- TOU Savings
- Peak Demand
Charge
Reduction
- Grid Peak
- Economic
- Reliability
- Emergency
Design
- Efficient Shell,
Equipment &
Systems
Operations
- Integrated
System
Operations
-Low Power Design
Dynamic
Control
Capability
- Demand Limiting
- Demand Shifting
- Demand
Shedding
- Demand
Shifting
4
Load Profiles and Terminology
Efficiency and Conservation
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15
Load Shedding
Energy Efficient
Baseline
Baseline
Demand Shedding
Load Shifting
16 17 18 19 20 21 22 23 24
p
Time of Day
gy
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19 20
21 22
23 24
Ti me of D a y
Baseline
Demand Shif t ing
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Ti me of D a y
15
16
17
18
19 20
21 22
23 24
5
Value of Demand Response
Utility Systems and Societal Value
•
•
•
•
Improve Reliability of the System
Reduce Electricity Costs and Market Efficiency
Risk Management
Environmental Impact
6
Value of Demand Response
Buildings Industry Opportunity
• Controls - Leverage investments combining
efficiency and DR capabilities, facilitate Zero
Energy Buildings (ZEB)
• Energy Information - Leverage knowledge of
electric load shape and energy use patterns, Link
to commissioning
7
Commercial Buildings’ Contribution to
Peak Demand
• Commercial sector
major role, may
dominate peak
demand, but data
lacking
Residential,
35%
Industrial,
19%
Commercial,
45%
Source: NEMS 2003 Simulation
8
Commercial Buildings’ Contribution to
Peak Demand
• Commercial
Buildings Energy
Consumption
Survey (CBECS) vs.
National Energy
Modeling System
(NEMS)
1995
(GW)
2003
(GW)
CBECS (1)
273
333
CBECS (2)
317
387
NEMS
Coincident
291
328
NEMS
Non-coincident
317
363
9
1/3 of Commercial Building Stock has
Energy Management Control System
(some “DR Ready”)
70.00%
31%
w/ EMCS
60.00%
w/o EMCS
69%
Source: CBECS 2003
% Buildings w/EMCS
50.00%
40.00%
30.00%
20.00%
10.00%
0.00%
1-5 K
5-10 K
10-25 K 25-50 K 50 - 100
Building Size (sqft.)
100 200
200 500
Over
500
10 K
Automated Demand Response in Large
Facilities
Goal: Evaluate feasibility of Automated DR hardware & software
systems in large facilities
• Can control & communications systems receive signals &
execute automated shedding?
• Control strategies for max load sheds & min service loss?
R&D Team: LBNL, Infotility, Akuacom, Shockman Consulting
0.70
Hi gh Price
0.50
0.40
M o de ra te
P ric e
0.30
P a rt-P e a k x 3
0.20
0.10
Off-P e a k
N orm al TOU
P a rt-P e a k
On-P e a k
N on-C PP D ay
P a rt-P e a k
0:00
23:00
22:00
21:00
20:00
19:00
18:00
17:00
16:00
15:00
14:00
13:00
12:00
11:00
9:00
10:00
8:00
7:00
6:00
5:00
4:00
3:00
2:00
1:00
0.00
0:00
Electricity Price [$/k Wh]
On-P e a k x 5
0.60
Off-
C PP D ay
11
2003, 2004 and 2005 Auto-DR System
Price Server
1.
2.
3.
4.
LBNL defines price schedule
Price published on XML (eXtensible
Markup Language) server
Clients request price from server
every minute & send shed
commands
EMCS carries out shed
automatically
Polling Client &
IP-Relay Software
2
3
Infotility
1
Internet
& private WANs
LBNL
Price Scheduler
IPRelay
Gateway
Polling
Client
Internet and
Private WANs
3
EMCS
Protocol
C
EMCS Protocol
4
C
C
4
C
C
Electric Loads
= Price Client
= Pilot site
= Price Server
= Development Site
C
C
Electric Loads
Test
Sites
C = EMCS Controllers
2003 test was Gateway only
2004 was Gateway or Relay
2005 both
12
Project Phases
• 2003 – 5 Sites (all Gateway Connectivity)
• Demonstrated basic concept and technical feasibility
• 2004 – 18 sites (13 Gateway, 5 Internet Relay)
• Demonstrated greater diversity in building systems and
DR shed strategies
• 2005 – 12 sites, Automated CPP with PG&E
• Demonstrated compatibility with utility DR programs
• 3 XML Gateways, 9 Internet Relays
• 2006 – Plans to Scale Up Field Tests with California
Utilities
• Target 40 sites with PG&E, discussions with SCE and SDG&E
• Evaluate economics, reliability, market size, market barriers
13
Results on Automated-DR
Aggregated Demand Saving, Sept 8th
7000
6000
5000
4000
3000
2000
1000
Albertsons
B of A (B)
Roche
USCB
Total Savings
23:00
22:00
21:00
20:00
19:00
18:00
17:00
16:00
15:00
14:00
13:00
12:00
11:00
9:00
OFB
10:00
8:00
7:00
6:00
5:00
4:00
3:00
2:00
1:00
0
0:00
Demand [kW]
• Established capabilities of
current controls and
communications with EMCS
and XML
• Demonstrated initial design of
signaling infrastructure and
system capability
• Demonstrated large sheds can
take place without complaints
• Demonstrated range of
strategies to produce sheds
and capabilities needed
• Average reduction 8%
• Range up to 56% reduction
Baseline
Number
of sites
Average
Savings
(%)
Max.
Savings
(%)
2003
5
8
28
2004
18
7
56
2005
12
10
38
14
1.60
1.40
1.20
1.00
0.80
0.60
0.40
0.20
Zone Setpoint Reset
Direct Fan/Chiller Control
Echelon
Cal EPA
Albertsons
USPS
Roche
Echelon
Cal EPA
B of A
GSA OFB
Summit Ctr
0.00
50 Doug
Maximum Demand Saving Intensity [W/ft2]
End-Use Data for Selected Sub-sample
Need Additional Field Studies
Lighting Shed
15
lo
b
SA al t
T em
Fa inc p.
n rea ad
D VFD se just
uc
m
en
t s lim
R ta i t
t
oo ti
fto c p
C
H p u res
W n .
C te it s red
H m h
W p ut uc
C cu . in do tio
hi
n
lle rre cre wn
Bo r d nt as
ile em lim e
Pr r lo an it
e- ck d
l
Ex coo out imi
t
te lin
g
n
Sl de
ow d
C re she
om co d
v p
O mo ery eri
ffi n
od
ce a
ar rea
ea lig
lig ht
ht di
di m
m
G
Auto-CPP DR Strategies by Sites (2005)
Office A
Office B
Office C
Office D
Office E
Office F
Office G
Office H
Office I
Retail A
Retail B
Post Office
Museum
High School
Data Center
16
Time Period
2 ºF -15 minutes
3 ºF - 30 minutes
4 ºF - 1 hour
5 ºF - 2 hours
6 ºF - 4 hours
4.5
4000
4.0
3500
3.5
3000
3.0
2500
2.5
2000
2.0
1500
1.5
1000
1.0
500
0.5
0
0.0
Actual
Baseline
Average of ~800 kW, 0.8 W/ft2 > 20% shed
for 3 hrs. by set point increase 72 F to 78 F
17
Power Intensity [W/ft2]
ASHRAE 55-2004,
Paragraph 5.2.5.2
Change in Temp
4500
0:00
1:00
2:00
3:00
4:00
5:00
6:00
7:00
8:00
9:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
18:00
19:00
20:00
21:00
22:00
23:00
Global Temperature Adjustment
of EMCS proposed for 2008
California Building Energy
Efficiency Standards
(Title 24)
Whole Building Power [kW]
Greatest Potential from Global
Temperature Adjustment
New York Times HQ Building
NY Times/ Renzo Piano/
Fox & Fowle/ Gensler/ Flack+Kurtz/
Susan Brady Lighting
The Challenge
•
•
•
•
Integrated shading & dimming
Under floor air systems
Commissioning in mockup
Field test supported by
NYSERDA, DOE, and CEC
Demand Response
• EnergyPlus simulations of DR
strategies
• Commissioning and controls
plans for DR strategies
18
The New York Times Building
Strategies -> Sequence of operations
• Lighting Level 1: Reducing lighting to 50% in core, 70% in PC
dominated interior and perimeter zones.
• Lighting Level 2: Reducing lighting to 50% in core, 70% in
interior zones and off in perimeter zones.
• Temperature Setup 1: Cooling set point increase from 74F to
76.5F
• Temperature Setup 2: Cooling set point increase to 78.5F
• Fan Box: Reduce perimeter fan boxes to 30% capacity from
2pm. to 6pm.
• Supply Temperature: Cooling supply temperature is set to 54
F until 2 pm. At 2 pm, it is increased to 59.5 F until 6pm.
19
Existing and New Dynamic Operational
Modes
• Operational modes implemented with EMCS
• Current Systems
•
•
•
•
Occupied/Unoccupied
Maintenance/Cleaning
Warm up/Cool down
Night purge
• Advanced– Integrated Master Controls Æ FINANCIAL FEEDBACK
• Daily cost minimization and IEQ optimization- non-DR Day
• Cost Minimization in Demand Response Mode (modify IEQ for short term)
• Cost minimization for On-Site Generation (dynamic control)
• Master Controls needed to integrate HVAC, Lighting,
Façade - Currently not intelligent, no decision making is
required
• Zero Energy Buildings – Same dynamic control needed for
grid power or on-site power
20
National R&D Opportunities
Advanced Controls for DR and Efficiency
Daily Peak Load Management
Systems and
Strategies
Energy Efficient
Systems and
Strategies
DR
Systems and
Strategies
21
Summary
• Demand Response and Dynamic Pricing growing nationwide
• DR capabilities in buildings revolve around controls!
• Field tests show DR potential 5-10% in many buildings with EMCS,
yet limited knowledge on how to develop strategies
• Research needed to evaluate DR control capabilities in broader
stock, control vintage, upgrade capabilities, market segments, and
new construction.
• National and Regional leadership needed to collaborate with
controls, engineering, and buildings industries, government
buildings early adopters
• DR is not driver, high performing buildings are:
• Low energy costs, well-commissioned, low maintenance costs
• Key is advanced controls, feedback systems, integrated
performance
• Controls for Zero Energy Buildings have common goals as DR
controls
22