Transcript CSC Energy Program – Financial Projections

National Town Meeting on Demand Response and Smart Grid – Washington, DC
Smart Buildings for a Smart Grid
Technology & Services to Make Buildings Grid Responsive
James Dagley,
Vice President of Channel Marketing and Strategy
June 24, 2010
Intro to Johnson Controls
140,000 Employees
Fortune 100

Founded in 1885 by Warren Johnson, inventor of the
first electric room thermostat

Over 40,000 employees dedicated to building
efficiency in 500+ locations in 125 countries



Market leader in HVAC and controls technology

Largest ESCO in North America with over $4.9
billion of active cost savings guarantees
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13,000 HVAC technicians, 12,000 facility mgrs
Over 1.4B sq ft of space under direct management,
with services provided to a further 20B sq ft
Multi-Industry Company
Agenda for Today’s Discussion
• Demand Response – the Market Opportunity
• The Building Perspective on DR
• Technology as the Key Enabler
• Example of Automated Demand Response
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Technology makes the smart grid possible…
.
…and buildings are the next wave
Source: Johnson Controls analysis of $3.4 billion in SGIG awarded October 2009
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Commercial buildings – big load, large potential
U.S. Electricity Demand (GW)
Half of U.S. peak demand is medium
to large facilities (>20 kW)
Potential Impact of DR (10-yr)
Large C&I
Residential
4%
Medium C&I
Small C&I
Source:North American Electric Reliability Corporation (2009) “2009 Summer Reliability Assessment”
FERC (2009) “A National Assessment of Demand Response Potential”
5
20%
The Building Perspective on Demand Response
What do mid to large commercial buildings require in order to
be interested in DR?
• Cost-Effective – economics have to work out
• Convenient – building operators cannot take on a “second job” to
manage load shedding
• Control – unwilling to allow outside parties (utility, service
provider, etc) complete control over load
CostEffective
Demand Response technology
can help with all three
Technology
Convenient
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Control
Cost-effective – Automating DR on operations budgets
Installation cost for DR automation technology
Site 12
Site 11
Median payback
of projects under
PG&E’s Auto-DR
program is 2.25
years
Site 10
Site 9
Site 8
Site 7
Site 6
Site 5
Site 4
Site 3
Site 2
Site 1
0
2000
4000
6000
8000
Up-Front Cost ($)
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Source: PG&E/LBNL AutoDR Pilot, 2006.
10000
12000
14000
Convenient – If it’s not easy, no one will do it
5% load response
without technology
vs.
10% load response
with auto-DR
technology
Two pilot studies show that automation leads to better response
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Source: Global Energy Partners (2007) “PG&E 2007 Auto-DR Program Assessment”
2006 CRA SPP C&I Report; Demand Response Research Center
Control – A “Spectrum” of Demand Response Options
Logic, decision-making and control can sit with the load-serving entity, the
customer, or anywhere between (e.g. an curtailment service provider):
Central Control
Direct Load
Control
(AC Cycling)
Autonomous Control
Interruptible Rate
Critical Peak Pricing
Wholesale Capacity
Programs
Wholesale Energy
Programs
Traditional “Aggregator”
Model
Voluntary Demand
Bidding
Pure Real Time Price
Historical DR has been centrally controlled, but there is a push to the
right of the spectrum. Buildings benefit.
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Technology can help with cost-effectiveness,
increase convenience and maintain control
Market-Based
Event-Based
Fixed Time of Use Pricing
Critical Peak Pricing
Demand/Capacity Bidding
Dynamic Pricing (RTP)
Direct Load Control
Curtailment/Interruptible Rate
Demand Limiting
Smart
Grid
BMS
Integrated Supervisory Control
Energy Storage
Energy Loads
Onsite Generation
-Set Points -On/Off
Minimize Energy Cost
Maximize Comfort
Building owner pre-defines load reduction strategies, levels and
thresholds based on and comfort and cost preferences
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An example of an automated demand response event
1
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High summer temps
drive up cooling loads
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Marginal cost of power
increases, T&D systems
become congested
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Provides real-time
visibility to building
managers
4
Ensures fans don’t
overcompensate for 6
new CHW set points
¢ per kWh
Throttles servers
for non-critical
applications
2
Automatically
dims lighting
Dispatches thermal
storage or gen-sets in
response to loss in
solar PV output
15¢
Hourly Prices for 7/1/09
3
10¢
5¢
12 3
am
9 12 3
pm
6
9
Curtailment signal or real time
price provided by ISO/utility
5
Adjusts space temp,
and chilled water
temp set points
10
11
6
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Prevents
PHEVs from
charging
during peak
hours
Case Study – Automated Demand Response:
Georgia Institute of Technology
• Georgia Institute of Technology is on a
dynamic hourly tariff from Georgia Power
• Each hour, building management system
reads prices for for next 48 hours from
utility’s web service feed
• Facilities director sets price threshold for
automated load shedding mode
Savings during initial summer 2006 pilot
Observing a 1MW peak load reduction, ~7% of load for participating buildings
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Thank You
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