∑
SEABORG – GRANGER
DEDICATION
IS ENERGY EFFICIENCY NECESSARY?
Dr Shoumen Datta
School of Engineering
Massachusetts Institute of Technology
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
1
US Energy Flow about 100 Ej per year : Lost Energy is nearly 60%
Source:
Livermore
National Laboratory
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation
& Lawrence
MIT School
of Engineering
2
Illustrative Mitigation Portfolios for Stabilization of GHG Concentrations 2000-2100
www.ipcc.ch/graphics/gr-ar4-syr.htm
ENERGY
EFFICIENCY
FOSSIL
FUEL
SWITCH
RENEWABLES
NUCLEAR
CCS
FOREST
SINKS
NON-CO2
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT
Forum for emission
Supply Chain
Innovation
& MIT–School
Cumulative
reduction
(GtCO
eq) of Engineering
2
3
www.ipcc.ch/graphics/gr-ar4-syr.htm
Illustrative
Mitigation
Portfolios for
Stabilization
of GHG
Cumulative
emission
(GtCO>2 MIT
– eq)
Dr Shoumen Palit
Austin Dattareduction
< shoumen@mit.edu
Forum for Supply Chain Innovation & MIT School of Engineering
4
ENERGY CONSUMPTION ANALYSIS
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
5
3717 TWh (2008)
US Electricity Use
2008 1403 TWh
38% Residential
2008 1350 TWh
36% Commercial
2008 960 TWh
26% Industrial
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering Source: US DOE
6
Where in USA?
3717 TWh 2008
Electricity Used
2008 1403 TWh
38% Residential
14%
23%
2008 1350 TWh
36% Commercial
45%
18%
2008 960 TWh
26% Industrial
3,717 TWh (2008)
Dr
Palit AustinUsed
Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
USShoumen
Electricity
7
Source: US DOE
~4700 terawatt-hours
26%
~3700 tWh
US Department of Energy
Energy Information Administration
Annual Energy Outlook 2008
Electricity Consumption Forecast 2030
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
8
~6500 terawatt-hours
Why Energy Efficiency
US Department of Energy
Energy Information Administration
Annual Energy Outlook 2008
Electricity Consumption Forecast 2030
Macroeconomic Drivers::
GDP
Population
Employment
Housing Starts
Construction
Exports
~4700 terawatt-hours
Annual Growth Rate
8
~3700 tWh
6
4
1950-1973
7 . 80 %
1974-2007
2 . 30 %
2008-2030
1 . 07 %
Middle-East Oil Embargo
1973-1974
2
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
0
9
~ 4,900
Source: US DOE
~ 4,700
~ 4,500
~ 4,300
US Energy Efficiency Savings Potential ~600 tWh
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
10
~ 4,900
Source: US DOE
~ 4,700
$20B $60B
~ 4,500
2015 $20 Billion
~ 4,300
2015 $10 Billion
2010 $10 Billion
US Partial Annual Energy Savings $20-60 billion 2030 @ 10 cents per kWh
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
11
The Business Case: Energy Efficiency Market
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
12
Electricity Grid
Source: US DOE
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
13
Data Granularity: Key to Energy Efficiency
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering Source: US14
DOE
Defining Energy Efficiency Target - Electricity Consumption 2008
US Department of Energy
Dr Shoumen
Palit Administration
Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
Energy
Information
15
Energy Efficiency Measures: Realistic Achievable Potential
Savings from Lighting and HVAC [2008 >150 tWh (~ $15 billion)]
Recommended Residential Measures
Recommended Commercial - Industrial Measures
Efficient lighting and HVAC controls
Efficient lighting and HVAC controls
Efficient space, water heating (heat pumps)
Efficient appliances (IT equipment, electronics,
refrigerators, dishwashers, washer-dryer)
Duct repair, insulation, fans, faucet, showerheads
Reflective roof, storm doors, external shades
High-efficiency windows (self-cooling/self-heating)
Efficient space, water heating (heat pumps)
Efficient appliances (IT equipment, electronics)
Duct repair, insulation, fans, faucet
Reflective roof, storm doors, external shades
High-efficiency windows
High-efficiency motors and drives
Residential Sector Measures
Efficient air conditioning
(central, room, heat pump)
Efficient space heating (heat pumps)
Efficient water heating (e.g. heat pump water
heaters & solar water heating)
Efficient appliances (refrigerators, freezers,
dishwashers, clothes washers, clothes dryers)
Efficient lighting (CFL, LED, linear fluorescent)
Efficient power supplies for consumer electronics
Air conditioning maintenance
Heat pump maintenance
Duct repair and insulation Infiltration control
Whole-house and ceiling fans
Reflective roof, storm doors, external shades
Roof, wall and foundation insulation
High-efficiency windows
Faucet aerators and low-flow showerheads
Pipe insulation
Programmable thermostats
In-home energy displays
Commercial Sector Measures
Efficient cooling equipment (chillers, central AC)
Efficient space heating (heat pumps)
Efficient water heating equipment (heat pumps)
Efficient refrigeration equipment & controls (e.g.
efficient compressors, floating head pressure
controls, anti-sweat heater controls, etc.)
Efficient lighting (CFL, LED, linear fluorescent)
Efficient lighting (interior and exterior; LED exit
signs, task lighting)
Efficient power supplies IT, electronics, office equipment
Lighting controls (occupancy sensors, daylighting)
AC maintenance
Water temperature reset
Efficient ventilation (air handling, pumps;
variable air volume)
Economizers and energy management systems
Programmable thermostats
Duct insulation
Retro-commissioning
High efficiency motors and drives
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
Source: EPRI,16
DOE
Energy Efficiency Framework for Savings
Objectives
Observations
Utility Analysis
Suggested Measures
Evaluation
Verification
Goals - Optimization
NRG eBusiness Service
Site Response
Energy Efficiency
Tools – Technology
Economic Analysis
Savings & ROI
Controls Automation
PILOT
Θ
• SWSN - Operation
• Monitor - Baseline
• Control - Reduce
• Savings - Credits
Evaluation & Analysis
Site Response
Θ
Savings & Credits
Demand Response
Carbon Footprint
Baseline Metrics
iET-Mitochondria
Program Design
Cost & Timeline
Approvals
Commencement
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
© INGRID ENERGY
17
EPRI
Framework
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
18
Dynamic Pricing Optimization
Dr Shoumen
Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
Source:
EPRI
19
1200
800
400
Middle-East
MiddleOil Embargo
Source: EEI & DOE
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
20
Law of Constant Pricing : Is it sustainable ?
10
8
6
Real Retail Price for Electricity, US Annual Average (Source: US Department of Energy)
CENTS / KWH
(includes tax)
1965
1975
1985
1995
2005
2008
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
21
Residential Use (kWh)
Devices
to
Monitor
and
Control
with
USWSN
for
Savings
and
Carbon
Credits
Source:
US DOE
(2008)
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
22
RESIDENTIAL
HVAC + LIGHTING = 47%
Target
Devices
to
Monitor
and
Control
with
USWSN
for
Savings
and
Carbon
Credits
Green Card
Annual $10,000
HVACL 47%
Savings 10%
Actual $470
Source: US DOE
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
23
Commercial (kWh/sq ft)
HVAC
25%
LIGHTING
25%
Target
Devices
to
Monitor
and
Control
with
USWSN
for
Savings
and
Carbon
Credits
Source:
US DOE
HVAC + LIGHTING
50%
(2008) TOTAL
COMMERCIAL
Green Card
Annual $1M
HVACL 50%
Savings 10%
Actual $50,000
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
24
Industrial Energy Efficiency Market
Different Criteria for Optimization
Machine Drive
51%
Industrial
Different
Devices
to
Monitor
and
Control
with
USWSN
for
Savings
and
Carbon
Credits
HVAC + LIGHTING
16%
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
25
Energy Efficiency Market – Projection through 2030
RESIDENTIAL ENDEND-USE PROFILE : Impact of EISA
+ 46%
-
31%
Dr Shoumen
Source:
US DOEPalit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
26
Energy Efficiency Market – Projection through 2030
COMMERCIAL
HVAC+L
(GWH)
COMMERCIAL
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
Source: US DOE
27
US Industrial Sector
Electricity Forecast
(GWH)
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
Source: US DOE
28
Summer Opportunity: More Savings from Efficiency
Summer: HVACL
GW
GW
GW
Commercial (258 GW)
GW
80%
77%
14%
Residential (382 GW)
AC
58%
Machine Drive
68%
Summer ’08: HVAC + LIGHT
Residential 47% to 80%
Commercial 50% to 77%
Water Heating
Dr Shoumen Palit Austin Datta < shoumen@mit.edu
Forum
Supply Chain Innovation & MIT School of Engineering
Industrial> MIT16%
to for14%
12%
Source:
US29
DOE
US Energy Efficiency Potential
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
Source: US 30
DOE
US Energy Efficiency : Potential for Savings by Sector
Dr Shoumen
Source:
US DOE Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
31
Realistic Achievable Potential for
Savings from Energy Efficiency
(GWh)
(GWh)
(GWh)
min
max
Market Value of
Energy Efficiency *
US WSN Monitoring
& Control is a subset
of Energy Efficiency *
Source: US DOE
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
32
US Energy Efficiency Potential to Reduce Summer Peak Demand
Key Value of Energy Efficiency:
Utilities must build capacity to
Dr Shoumen
33
Source:
US DOEPalit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
exceed summer peak demand.
Summer Peak Demand Savings from Energy Efficiency & Demand Response
(GW)
(GW)
(GW)
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
Source: US 34
DOE
Residential Efficiency
Market
Acceptance
Ratios
Source: US DOE
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
35
Commercial Efficiency
Market
Acceptance
Ratios
Source: US DOE
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
36
Industrial Efficiency
Market
Acceptance
Ratios
Source: US DOE
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
37
Residential
Program
Implementation
Factors
Source: US DOE
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
38
Commercial
Program
Implementation
Factors
Source: US DOE
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
39
Commercial
Program
Implementation
Factors
Source: US DOE
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
40
Industrial
Program
Implementation
Factors
Source: US DOE
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
41
Energy Efficiency 2030
Realistic Achievable Potential
Source: US DOE
42
Annual Electricity Savings Relative to Baseline (TWh)
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
RESIDENTIAL
Realistic Achievable Potential
Annual Electricity Savings tWh
20
40
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
Source: US DOE
60
43
COMMERCIAL
Realistic Achievable Potential
Annual Electricity Savings tWh
20
40
60
80
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
44DOE
Source: US
Source: US DOE
INDUSTRIAL
Realistic Achievable Potential
Annual Electricity Savings tWh
40
20
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
60
45
Data Granularity: Key to Energy Efficiency from Demand Response
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering Source: US46
DOE
US Demand Response
Realistic Achievable Potential
Cumulative Summer Peak Demand Savings (MW)
5K
10K
15K
Dr
Shoumen
Source:
US DOE Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
47
USWSN ENERGY TRANSPARENCY : DEMAND-RESPONSE
readers sensors
tools
mall
school factory buildings
DATA
Zone 2
Zone 1
Metropolis
County
DATA
Data
State
Province
Decisions
DECISIONS
DECISIONS
DECISIONS
COUNTRY
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
48
US Demand Response
Realistic Achievable Potential
Cumulative Summer Peak Demand Savings (MW)
$60B
$40B
$20B
2010
2020
2030
COST (Estimated)
5K
10K
15K
Dr
Shoumen
Source:
US DOE Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
49
Source: US DOE
Do we expect customers to respond to:
Intelligent Energy Transparency (iET)
Savings from Monitor and Control
Carbon Credits
1,219 TWh
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
50
Source: Gillingham, K., Newell, R. and Palmer, K. (2006) Energy Efficiency Policies: A Retrospective Examination. Ann Rev of Environ & Resources 31 161–192
Business Risk in Efficiency: Forecasting Errors
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
51
Middle-East
MiddleOil Embargo
Source:
Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
USDr
DOE
52
Middle-East
MiddleOil Embargo
Source:
Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
USDr
DOE
53
Middle-East
MiddleOil Embargo
Source:
Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
USDr
DOE
54
Energy Efficiency ?
North Korea
Source: US DOE
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
55
CIA Fact Book
Top 10 Oil Importers
Rank
Countries
United States:
#1
#2
Japan:
Germany:
#3
#4
#5
#6
#7
#8
#9
#10
Amount
10,400,000 barrels per day
5,300,000 barrels per day
2,600,000 barrels per day
France:
1,850,000 barrels per day
Italy:
1,690,000 barrels per day
China:
1,600,000 barrels per day
Spain:
1,500,000 barrels per day
India:
1,200,000 barrels per day
Turkey:
584,326 barrels per day
Thailand:
539,973 barrels per day
Unsustainable trajectory for developing nations: eg Thailand
Total energy imports 11% of GDP 2006 (9.9% GDP in 2005)
56
Channel NewsAsia 19 July 2007
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
Enabling Tools and Technology
Energy Efficiency:
US WSN
◊ ROI
◊ Savings
◊ Carbon Credits
◊ Methodology & Certification
◊
Ubiquitous Secure Wireless Sensor Networks
Return on Investment
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
57
Device detection
Consumption profile
Usage parameters
Control commands
Monitor execution
Savings & Analytics
Light
a
Temperature
b
Humidity
Automatic control
function(a,b,c)
•Ideal light
•Ideal temperature
•Ideal humidity
c
Gateway
INGRID
MOBILE
Did I turn off the kitchen stove in my flat?
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
58
Generating intelligent reports using data mining technology
INGRID
ENERGY
Analysis and announce of
system efficiency monitor
Early warning of system
exception
Analysis for power
consumption
Parameter Analysis of
environmental sensor
Customization reports for
warning and monitor data
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
59
Energy Conservation: Utility Landscape
Spot Markets
(Procurement)
Cost / KWH
Energy Operations
Weather
Forecast
Building
Cooperative
INTERNET
Generation
Transmission
Contract / Bill
Procurement
Audit
Energy Management
Systems
Business Services
Building
Management System
Bills – Audit
Energy Analytics
HVAC Light Sprinkler
LIFTS Fire Security
MEMS Installers
Distributed Generation
Analysts - Lawyers
Factory / Building / Facility / Apartment / Shopping Mall / Hotel
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
60
Energy Efficiency : Optimization -Aggregation
Demand – Response
Carbon Credits
Measure, Monitor, Audit, Control, Save, Micro-credits
Building
Campus
Enterprise
Deployment
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
61
Industry History
Kyoto Protocol proposed, 1992
Kyoto Protocol adopted, 1997
Kyoto Protocol in effect, 2005
Beyond 2005 Intelligent Energy Transparency [ iET ]
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
62
Facilities Hierarchy Model
P. Ehrlich
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
63
HIERARCHY
GRANULARITY
∑
Intelligent
Agents
Building
Automation
System
Financial
Analytics
Real-time
Monitoring
SCADA
Energy Consuming
Devices
Meters
INTERNET
Real-time DB
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
64
Field Devices:
Systems Integration
DB
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
65
Knowledge Management
• Knowledge from energy managers
• Strategies relating to Occupancy, Water Pressure, Light,
•
Duct Pressure, Precooling, Thermal Strategies, etc.
Acquisition tools
• Representing acquired strategies in AI systems
(rule based and goal based) as heuristics
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
66
iET 101
-
Schedule: start chiller at 0430 am at 55F
Simple light sensor: sun comes up, switch off parking lot lights
Feedback: keep zone 1 temperature between 68F to 72F
Algorithms: compounds of the above
But allow
Neural Network Learning - Predictions
Heuristics [re-arranging living room with spouse] aren’t algorithms.
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
67
iET: Expert Systems and Neural Networks based on Goals
Weather Forecast, Price of Energy
Goals as
Triggers
Business
As Usual
Emergency
Curtailment
Strategy Agents:
Light, Pre-cool, SAT
Agent
Decisions
Device
Forecaster
Neural Net
Forecasts
Device
Read/Write
Sensor Data
Device
Proxy
Control
Signal
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
68
GLOBAL
CLOUD
COMPUTING
ANALYTICS
21DA : 00D3 : 0000 : 2F3B : 02AA : 00FF : FE28 : 9C5A
LOCAL
CLOUD
COMPUTING
21DA : 00D3 : 0000 : 2F3B : 02AA : 00FF : FE28 : 9C5A
21DA : 00D3 : 0000 : 2F3B : 02AA : 00FF : FE28 : 9C5B
IPv6
Emergence of
MITOCHONDRIA
21DA : 00D3 : 0000 : 2F3B : 02AA : 00FF : FE28 : 9C5A
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
21DA : 00D3 : 0000 : 2F3B : 02AA : 00FF : FE28 : 9C5C
69
21DA : 00D3 : 0000 : 2F3B : 02AA : 00FF : FE28 : 9C5D
Conceptual Energy Box: Dynamic Optimization
Aggregation for Energy Efficiency and Savings
Batteries
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
70
Continuous ANN Training: Predicted vs Observed
D. Mahling
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
71
Demand Forecast
D. Mahling
Intelligent Use of Energy
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
72
Agent
SAT
SAT
SAT
SAT
Space
Temp
kw
69
40
69
40
69
40
69
37
11:16
69
37
11:18
69
37
11:20
69.5
37
69.5
40
11:24
69.5
40
11:26
69.5
40
11:28
69.5
40
11:30
69
40
Device
Time
Wellness
AHU08
11:10
Wellness
AHU08
Wellness
AHU08
Wellness
AHU08
Wellness
AHU08
Wellness
AHU08
Wellness
AHU08
Wellness
AHU08
Wellness
AHU08
Wellness
AHU08
Wellness
AHU08
Wellness
AHU08
11:12
11:13
11:14
11:22
Command
Presetting SAT
Reset to 58
Setting SAT
Register to 1
Writing SAT
Reset 60
Setting SAT
Register to 0
SAT
at work
D. Mahling
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
73
Case Study: AI for Demand Response
• Electronic signal was sent from CA-ISO to building system
– curtail 2 Megawatts of load for 4 hours across 78 retail sites
• Base load for 78 properties approx 10 Megawatts
• Signal received at 1:45 PM [15 minutes ahead of the start time of 2PM]
• Curtailment commenced at 2PM and completed at 6PM PDST
D. Mahling
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
74
Sequence of Events
•
•
•
•
•
•
•
•
•
•
•
•
•
1:45 – DR signal received
1:46 – Agents shift from BAU mode to curtailment mode
1:47 – Energy Operator dials in 2 MW curtailment goal
2:00 – L/R agent deploys speed reduction on largest fans in North and South
2:10 – 1MW reduction
2:15 – Agent releases first L/R; Agent assembles second L/R set; deploys
2:20 – 2MW reduction
Repeats until 3pm
3:00 – SAT agent raises SAT at select buildings
3:15 – SAT shifts buildings
3:05 – 1.2 MW reduction
3:20 – L/R rotates groups
Etc
D. Mahling
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
75
Curtailment: Trend Data and Energy Savings
D. Mahling
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
76
AI based systems learn to further reduce energy use
D. Mahling
30% Reduction
15% Reduction
The electric demand was reduced by 15% below the Martin Luther King Holiday or 30% over a typical Monday.
There was an additional financial benefit from reducing electric demand prior to the holiday (Fri/Sat/Sun).
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
77
Ubiquitous Secure Wireless Sensor Network
Sensors distributed over a wide range
Multiple dynamics and penetration of barriers
No single point of failure
Grid power not necessary
Bi-directional data monitoring, reset, reconfiguration, control
Useful to manage:
Energy Efficiency
Security & Safety
Healthcare
Site
Controller
Internet
Server
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
S. Rhee
78
ENERGY EFFICIENCY: Preliminary Solutions Approach
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
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Answers, not numbers: Immediate Customer Satisfaction
BEFORE
VERY
COLD
Optimize
AFTER
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FUTURE OF ENERGY EFFICIENCY:
A Global Network Systems Solutions Approach
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81
Data Granularity: Key to Energy Efficiency
Energy
Decision
Systems
Data Granularity: Key to Energy Efficiency
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering Source: US25
DOE
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Foru m for Supply Chain Innovation & MIT School of Engineering Source: US25
DOE
Energy Decision Systems
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
82
Volatility of SupplySupply-Demand: Insufficient Data Granularity
Source:
Dr Shoumen
MIT Portugal
Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
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Wireless Sensor Networks in Energy Efficiency: Data Granularity
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
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User
Firewall
Sensor
Data
LOCAL
System
Firewall
Cost / kWh
Data
Application
Logic
Emissions
GHG Data
GLOBAL
Mapping
Function
Carbon
Credits
Distributed
Datamarts
Dr Shoumen Palit Austin Datta
Energy Efficiency
Decisions
< shoumen@mit.eduIntelligent
> MIT Forum for
Supply Chain Innovation & MIT School of Engineering
85
Network Software Systems
Energy Efficiency:
Intelligent Decisions
Control
(Global)
Data
(Boston)
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
86
SUMMARY: Temporary Advantages
• Implement WSN to monitor and record
carbon emissions for carbon footprint audit
• Profit from control to improve savings and incentives due to
energy efficiency or conservation measures
• Install carbon reduction management tool (iET) to balance
carbon liabilities in commercial/industrial risk management
• Innovate on carbon trading options through cooperatives of
carbon micro-credits
• Optimize ROI through energy savings, carbon credits and
alternative energy portfolio (user and supplier)
• Interface with grid to curtail volatility and dynamic pricing
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
87
Submission of article for consideration of UNFCCC – UN Climate Summit 2009
QUEST FOR INTELLIGENT MITOCHONDRIA
http://dspace.mit.edu/handle/1721.1/45552
UNFCCC
Programs
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
88
Acknowledgements
✍ MIT Building Technology Program
Dr D. Mahling and Mr S. Samohous
✍ MIT Field Intelligence Laboratory
Professor Sanjay Sarma
✍ MIT Energy Initiative
✍ MIT Forum for Supply Chain Innovation
✍ Bureau of Energy Efficiency, Government of India
Dr Ajay Mathur
✍ UN Climate Congress, University of Copenhagen
Professor Katherine Richardson
✍ EMC2 Laboratory, Oak Ridge National Laboratory, US DOE
Dr Shoumen Palit Austin Datta < shoumen@mit.edu > MIT Forum for Supply Chain Innovation & MIT School of Engineering
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