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Sustainability?
Sustainable development should meet theneeds of the present without compromisingthe ability of future generations to meet theirown needs
Our Common Future, World Commission on Environmentand Development, United Nations, 1987
2 11/7/2012
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My Goal today
Suggest ways SenSys community is and canbe more engaged in achieving sustainableenergy networks
11/7/20123
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Quantifying Sustainability California Law
AB 32 Reduce GHG emissions to 1990 levels by 2020
Governors executive order S-3-05 (2005) 80% reduction below 1990 levels by 2050
Renewable Portfolio Standard 33% renewables by 2020, 20% biopower procurement
480 => 80 mmT CO2e in 40 years Population: 37 => 55 million Economic growth
11/7/20124
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CA2050: GHG 90% below 1990
5 11/7/2012
But,
0
200
400
600
800
1,000
1990 2005 2020 2050
Historical BAU
G H G E m i s s i o n s ( M t C O
2 e / y r )
Energy
emissionsNon-energyemissions2020 Target
2050 Target
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CA2050 4 Part GHG Reduction Plan
Efficiency
6 11/7/2012
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Efficiency Electrify
7 11/7/2012
CA2050 4 Part GHG Reduction Plan
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CA2050 4 Part GHG Reduction Plan
Efficiency Electrify Decarbonize
the electricity Decarbonize
the fuel
8 11/7/2012
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CA2050 4 Part GHG Reduction Plan
Efficiency Electrify Decarbonize
the electricity Decarbonize
the fuel
9 11/7/2012
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All required for even 60% reduction
but still fall short of 80%11/7/201210
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Scenarios
11 11/7/2012
New Nuclear plantevery 14 monthsfor 40 years
New CCS facilityevery 9 mo.Exceeds saline
aquifer
Resources exist- 1.4 % of CA land- 43% agriculture- 3.4% urban
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The Problem: Supply-Demand Match
12
Baseline + Dispatchable Tiers Oblivious Loads
TransmissionGeneration DemandDistribution
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An Engineering Marvel NA: 3 synchd regions Lots of wires
170k miles of >200 kvtransmission
6m miles of distribution
3k miles of 500 kv DC 3,200 retail
distributors 147 M customers
125M res, 17.6 M com,0.78 M ind.
10 ISO/RTO cover 2/3 Little communication
11/7/201213http://www.nerc.com/docs/oc/rs/BA_BubbleDiagram_2011-10-03.jpg
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Towards an Aware Energy Network
14
Baseline + Dispatchable Tiers Oblivious Loads
Communication
Non-DispatchableSources
Communication
Aware InteractiveLoads
TransmissionGeneration DemandDistribution
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Classic al view of the Energy Challenge
Supply Transport Load
Generators Lines
TransformersMeters
VFDEfficiency
Control
Baseline
Intermittent
Peaker
Nuclear,Coal
HydroGeothermal
Combined cyclenat. gas
Single cyclenat. gas
T r a n s m
i s s i o n
D i s t r i b u t i o n
Imports
Motors
Lighting
HVAC
Electronics
Appliance
Power Supplies
Markets
Circuits
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Modern Energy Network Challenges
Supply Transport Load
Generators Lines
TransformersMeters
VFDEfficiency
Control
Baseline
Intermittent
Peaker
FluctuatingRenewable
Nuclear ,Coal
HydroGeothermal
Combined cyclenat. gas / bio
Single cyclenat. gas /
bio
PhotovoltaicWind
T r a n s m
i s s i o n
D i s t r i b u t i o n
Imports
Motors
Lighting
HVAC
Electronics
Appliance
Power Supplies
Storage
Consumption
Usage
Schedule
Pricing
Facilities
Personal
Industrial
Transportation
Pumped
Information Plane
Physical Plane
FluctuatingRenewable
Storage Storage
Circui ts
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Sensys? Creating the info plane
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Smart Meters the WSN Killer App?
Supply Transport Load
Generators Lines
TransformersMeters
VFDEfficiency
Control
Baseline
Intermittent
Peaker
Nuclear,Coal
HydroGeothermal
Combined cyclenat. gas
Single cyclenat. gas
T r a n s m
i s s i o n
D i s t r i b u t i o n
Imports
Motors
Lighting
HVAC
Electronics
Appliance
Power Supplies
Markets
Circuits
11/7/201218
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Smart meter rollouts
11/7/201219http://www.edisonfoundation.net/iee/Documents/IEE_SmartMeterRollouts_0512.pdf
Proprietary / Zigbee
Open IPv6,
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Much more than meters and billing
11/7/201220
http://www.openthegrid.com/docs/ipv6_in_smart_grid_field_area.pdf
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The Mote/TinyOS revolution
SmartDustWeC Rene
Intelrene
9998 00 01 0302 04 0605 07
S E N S I T
E x p e d
i t i o n
N E S T
N E T S /
N O S S
C E N S
S T C
N S F
C y b e r -
P h y s i c a
l
Mica
Inte l/UCBdot
InteliMOTE
XBOWcc-dot
XBOWmica2
XBOWrene2
Intelcf-mica
Boschcc-mica
Dust Incblue cc-TI
digital sunrain-mica
XBOWmica
zeevo BT
TelosXBOWmicaZ
Intel
MOTE2EyesBTNod
etrio
8 kBrom kBram
48 kB rom10 kB ram802.15.4
L o W
P A N / I P v 6
Epic
11
I E T F R P L
10
11/7/2012
Mote inside uP => Arm Cortex Radio => 802.15.4gnarrow=bandfrequency hopper TinyOS too SOC from here
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23
Idle Listening: 3 Basic Solutions Scheduled Listening
Arrange a schedule of communication Time Slots Maintain coordinated clocks and schedule
Listen during specic slots Many variants:
Aloha, Token-Ring, TDMA, Beacons, Bluetooth piconets, S-MAC, T-MAC, PEDAMACS, TSMP, FPS,
Sampled Listening Listen for very short intervals to detect eminent
transmissions On detection, listen actively to receive DARPA packet radio, LPL, BMAC, XMAC, Maintain always on illusion, Robust
Listen after send (with powered infrastructure) After transmit to a receptive device, listen for a short time Many variants: 802.11 AMAT, Key fobs, remote modems,
Many hybrids possible
11/7/2012
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24
802.5Token Ring
Internet WSN assimilated
802.3Ethernet
802.11WiFi802.3a
Ethernet10b2802.3i
Ethernet10bT802.3y
Ethernet100bT802.3ab Ethernet1000bT
802.3an Ethernet
1G bT
802.11aWiFi802.11b
WiFi802.11g
WiFi802.11n
WiFi
X3T9.5FDDI
SerialModem
GPRS
ISDNDSL
Sonet
Transport (UDP/IP, TCP/IP)
Application (Telnet, FTP, SMTP, SNMP, HTTP)
Diverse Object and Data Models (HTML, XML, , BacNet, )
802.15.4LoWPAN
Network (IP)Link2: link
3: net
4: xport
7: app
1: phy
11/7/2012
802.15.4e
802.15.4gP1901.2
6LoWPAN RFC6282
RPL RFC6550
COAP
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Or in industry speak
11/7/201225
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At incredible scale
11/7/201226
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ROLL & Sensys Role RPL retained fundamental routing diversity
Multiple DODAGs with selection Incorporated trickle density awareness
Many questions for which the research was simply
not there Piece-wise source routing, routing stretch versus protocol
complexity & state, routing metrics, Many issues for which the analysis is seriously
incomplete Local / global repair, loop formation, routing staleness,
scaling, state management, trickle timers IETF, mobile, and industry rediscovering Where is the research community?
11/7/201227
k
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Creating an Energy Network ???
Supply Transport ConsumptionLoad
Generators Lines
TransformersMeters
VFDEfficiency
Usage
ScheduleControl
Pricing
Baseline
Intermittent
Peaker
FluctuatingRenewable
Nuclear ,Coal
HydroGeothermal
Combined cyclenat. gas / bio
Single cyclenat. gas /
bio
PhotovoltaicWind
T r a n s m
i s s i o n
D i s t r i b u t i o n
Imports
Motors
Lighting
HVAC
Electronics
ApplianceFacilities
Personal
Industrial
Transportation
Power Supplies
FluctuatingRenewable
Storage Storage Storage Pumped
Information Plane
Physical PlaneCircuits
11/7/201228
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Grid Exists
30
Conventional Electric Grid
GenerationTransmission
DistributionLoad
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Internet Exists
31
Conventional Electric Grid
GenerationTransmission
DistributionLoad
Conventional Internet
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Wh S ?
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Where to Start?
Buildings 72% of electrical consumption (US), 40-50% of total consumption, 42% of GHG footprint US commercial building consumption
doubled 1980-2000, 1.5x more by 2025[NREL]
Where Coal is used
Prime target of opportunity forrenewable supplies
33
Renewable energy consumption
Electricity source
11/7/2012
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Building Power Consumption
11%
1MW 883 kW
11/7/201234
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P
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11/7/201237
Power-Proportional
Buildings ? 1.45 MW 2.02 MW
Min = 72% of Max
Stanley Hall:Office + BioScience
- 13 NMRs
P
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11/7/201238
Power-Proportional
Buildings ? 756 KW 1030 KW
Min = 69% of Max
Koshland Hall:Office + ???
P
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11/7/201239
Power-Proportional
Buildings ?62 KW
202 KW
Min = 31% of Max
LeConte Hall: Office
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Power Proportionality
40
Productivity
C o n s u m p
t i o n
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Power Proportionality
41
Productivity
C o n s u m p
t i o n
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Doing Nothing Well ???
11/7/201242
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Power Proportional Buildings?
43
50 Ton Chiller 200 Ton Chiller
10 months 2 months
Scott McNally Bldg Manager 11/7/2012
The Building Challenge
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The Building Challenge
44
CT: mains
powermonitoringPanel 1 Panel 2
A
B
A
B
Panel 1 Panel 2
A
B
A
B
1
5
9
13
17
21
25
29
33
37
41
3
7
11
15
19
23
27
31
35
39
A1
5
9
13
17
21
25
29
33
37
41
3
7
11
15
19
23
27
31
35
39
1
5
9
13
17
21
25
29
33
37
41
3
7
11
15
19
23
27
31
35
39
A2
6
10
14
18
22
26
30
34
38
42
4
8
12
16
20
24
28
32
36
40
B2
6
10
14
18
22
26
30
34
38
42
4
8
12
16
20
24
28
32
36
40
2
6
10
14
18
22
26
30
34
38
42
4
8
12
16
20
24
28
32
36
40
B
1
5
9
13
17
21
25
29
33
37
41
3
7
11
15
19
23
27
31
35
39
A1
5
9
13
17
21
25
29
33
37
41
3
7
11
15
19
23
27
31
35
39
1
5
9
13
17
21
25
29
33
37
41
3
7
11
15
19
23
27
31
35
39
A2
6
10
14
18
22
26
30
34
38
42
4
8
12
16
20
24
28
32
36
40
B2
6
10
14
18
22
26
30
34
38
42
4
8
12
16
20
24
28
32
36
40
2
6
10
14
18
22
26
30
34
38
42
4
8
12
16
20
24
28
32
36
40
B
panel level powermonitoring
ACme: plug loadenergy monitor and
controller
Temperature
Humidity
Vibra;on
Pressure
E le c t r ic L o ad T r e e C lim a t e P la n t
Operations and Environment
11/7/2012
CEC B2G T tb d A E g
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CEC B2G Testbed - An EnergyTransparent Building
11/7/201245
Whole BldgMCL equip
MCL infra
MCL vac
servers
DOP HVAC
Central vent
office HVAC
inst Lab 199HVAC
Plug loads
Lighting
Parking Lot
The Other Energy Usage
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The Other Energy Usage
11/7/201246
Bldg 90
Wireless plug meters
on 611 of 1200 loads
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sMAP simple Monitoring and Action Protocol Uniform Access to Diverse Physical Information
11/7/201247
Electrical
Weather
GeographicalWater
EnvironmentalStructuralActuator
Occupancy
sMAP
Modeling
Visualization
ContinuousCommissioning
Control
PersonalFeedback
DebuggingStorageLocation
Authentication
Actuation
A p p
l i c a t
i o n s
P h y s
i c a l
I n f o r m a t
i o n
REST API
HTTP/TCP
JSON Objects
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Internet
Cell phonesMAP Gateway
sMAP
Modbus RS-485
sMAP
sMAP Gateway
EBHTTP / IPv6 / 6LowPANWireless Mesh Network
sMAP
sMAP
sMAP
sMAP
Edge Router
Temperature/PAR/TSR
Vibra;on / Humidity
AC plug meter
Light switch
D e n t c i r c u i t m e t e r
P r o x y S e r v e r
E B H T T P
T r a n s l a ; o n
California ISO sMAP Gateway
sMAP Resources Applica;ons
Google PowerMeter
Weather
sMAP
Every Building
Database
sMAP Virtual Energy-Lab Ecosystem
11/7/201248
Factoring is critical
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Factoring is critical
Archiver
RDBMS TSDB
sM
AP
sMAP
sMAP
c on
t r ol
w e b
6lowpannetworks
RS-458 bus
BacNET/IP
m o d el s
m g
m t
Public interfaces
Application-specificfunctionality built onexposed interfaces
Provide access toarchived data
Manage views, datacleaning
Represent, transmit dataand metadata
Abstract underlyingheterogeneity into simpledata model
11/7/201249
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sMAP is Universal information representation for physical
data Self-describing, compact JSON schema, transportable
over UDP/TCP Integrated metadata
Software Architecture for physical data processingand actuation Real-time and archival data, time-series DB Adapters/Drivers for legacy and direct streams Subscription, syndication, distillates Query processing, visualization interface
Resource-oriented web-service framework forembedded applications
50 11/7/2012
http://code.google.com/p/smap-data
All ph sic l info
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Name Sensor Type Access Method Channels
ISO Data CAISO, NYISO, PJM, MISO, ERCOT, BPA Web scrape 1211ACme devices Plug-load electric meter Wireless 6lowpan mesh 344
EECS submetering project Dent Instruments PowerScout 18 electric meters Modbus 4644
EECS steam and condensate Cadillac condensate; Central Station steam meter Modbus/TCP 13
UC Berkeley submetering feeds ION 6200, Obvius Aquisuite; PSL pQube,VerisIndustries E30
Mosbus/Ethernet, HTTP 4269
Sutardja Dai, Brower Hall BMS SiemensApogee BMS, Legrand WattStopper,Johnson Control BMS
BACnet/IP 4064
UC Davis submetering feeds Misc., Schneider Electric ION OPC-DA 34 (+)
Weather feeds Vaisala WXT520 rooftop weather station;Wunderground
SDI-12, LabJack/Modbus, webscrape
33
CBE PMP toolkit Dust motes; NewYork Times BMS CSV import; serial 874
NOA Weather Forecast Meteorological (window, solar, cloud, etc) Web 77740
SDH Air Quality CO2, Temp, TSR, PAR, Hum Wireless 6lowpan mesh 50
total: 93,242
All physical info
11/7/201251
www.openbms.org
Li i g L b A h I t i
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Living Lab Approach: Innovate in aVirtual Private Grid
GenerationTransmission
DistributionLoad
VPG
11/7/201252
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sMAP Energy Markets, Ops, $,
11/7/201253
http://www.isorto.org
BPA
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sMAP Solar, Wind, Meteorology
1450 Met feeds covering Cal Solar Initiative: 130,275 proj. 1370 MW
Cal Utility Solar: 60 facilities 695 MW Cal Utility Wind: 134 facilities 4295 MW
11/7/201254
MAP i
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sMAP generation CA generation plant locations, type, and
rated power (> 0.1 MW) [CEC] Hourly output from each type of CA
generation source for > 1 year [CAISO]
[CEC] http://energyalmanac.ca.gov/powerplants/Power_Plants.xls
[CAISO] http://www.caiso.com/green/renewableswatch.html11/7/201255
Modern Energy Network Challenges
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Modern Energy Network Challenges
Supply Transport ConsumptionLoad
Generators Lines
TransformersMeters
VFDEfficiency
Usage
ScheduleControl
Pricing
Baseline
Intermittent
Peaker
FluctuatingRenewable
Nuclear ,Coal
HydroGeothermal
Combined cyclenat. gas / bio
Single cyclenat. gas /
bio
PhotovoltaicWind
T r a n s m
i s s i o n
D i s t r i b u t i o n
Imports
Motors
Lighting
HVAC
Electronics
ApplianceFacilities
Personal
Industrial
Transportation
Power Supplies
FluctuatingRenewable
Storage Storage Storage Pumped
Information Plane
Physical PlaneCircuits
11/7/201256
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What would the CA Grid be like @
60% renewables?
11/7/201257
Bloomberg New Energy Finance, Liebreich April 5, 2011
G-20Investment
($B)
Whos Winning the Clean Energy Race? 2010 Pew Charitable Trust www.PewEnvironment.org/CleanEnergy
CA g id t d S li
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CA grid today - SuppliesSource Rated
(GW)
Capacity
Factor1
Total Energy
(TWh)
% of Total
EnergyGeothermal 2.600 38.7% 8.68 3.8%
Biomass/Biogas 1.145 43.5% 4.30
1.9%
Small Hydro 1.380 31.7% 3.77 1.7%
Wind 2.812 29.1% 7.06 3.1%
Solar 3 0.403 28.7% 1.00 0.4%
Nuclear 4.456 85.9% 33.00 14.6%
Hydro 12.574 27.7% 30.05 13.3%
Imports 11.055 2 66.6% 63.43 28.0%Thermal 44.339 19.7% 75.43 33.3%
Total 80.764 32.6% 226.71 100.0%1 Mean delivered power divided by rated power (excl. import)2 For imports, rating is the maximum observed power 3 Residential net factored into demand11/7/201258
CA g id t d S l Ch ll g
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CA grid today Supply Challenge
11/7/201259
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CA grid today Supplies
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CA grid today - SuppliesSource Rated
(GW)
Capacity
Factor1
Total Energy
(TWh)
% of Total
EnergyGeothermal 2.600 38.7% 8.68 3.8%
Biomass/Biogas 1.145 43.5% 4.30
1.9%
Small Hydro 1.380 31.7% 3.77 1.7%
Wind 2.812 29.1% 7.06 3.1%
Solar 3 0.403 28.7% 1.00 0.4%
Nuclear 4.456 85.9% 33.00 14.6%
Hydro 12.574 27.7% 30.05 13.3%
Imports 11.0552
66.6% 63.43 28.0%Thermal 44.339 19.7% 75.43 33.3%
Total 80.764 32.6% 226.71 100.0%1 Mean delivered power divided by rated power (excl. import)2 For imports, rating is the maximum observed power 3 Residential net factored into demand11/7/201261
A i h d id
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A year in the todays grid
11/7/201262
Seasonal, Weekly, DailyvariationsMany underlying factors
Peak: 47.1 GWMin: 18.8 GWMean: 26.3 GW
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A mid summers week
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A mid-summer s week
11/7/201264Sep Nov Jan Mar May Jul
0
10
20
30
40
50
60
70
T o
t a l C A P o w e r
( G W )
IMPORTS: 28.0%THERMAL: 33.3%WIND: 3.1%SOLAR: 0.4%BIOMASS/BIOGAS: 1.9%GEOTHERMAL: 3.8%HYDRO: 13.3%SMALL HYDRO: 1.7%NUCLEAR: 14.5%CA GRID DEMAND
07/08 07/09 07/10 07/11 07/12 07/130
5
10
15
20
25
30
35
40
45
T o t a
l C A P o w e r
( G W )
IMPORTS: 29.9%THERMAL: 26.2%
WIND: 5.0%SOLAR: 0.6%
BIOMASS/BIOGAS: 1.8%GEOTHERMAL: 3.2%
HYDRO: 15.9%SMALL HYDRO: 1.9%NUCLEAR: 15.4%CA GRID DEMAND
A winter weeks tale
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12/19 12/20 12/21 12/22 12/23 12/24
0
5
10
15
20
25
30
35
40
45
T o
t a l C A P o w e r
( G W )
IMPORTS: 24.5%
THERMAL: 38.5%
WIND: 1.8%
SOLAR: 0.1%
BIOMASS/BIOGAS: 1.9%
GEOTHERMAL: 4.0%HYDRO: 14.8%
SMALL HYDRO: 1.4%
NUCLEAR: 13.1%
CA GRID DEMAND
A winter week s tale
11/7/201265Sep Nov Jan Mar May Jul
0
10
20
30
40
50
60
70
T o
t a l C A P o w e r
( G W )
IMPORTS: 28.0%THERMAL: 33.3%WIND: 3.1%SOLAR: 0.4%BIOMASS/BIOGAS: 1.9%GEOTHERMAL: 3.8%HYDRO: 13.3%SMALL HYDRO: 1.7%NUCLEAR: 14.5%CA GRID DEMAND
Th D d D ti C
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The Demand Duration Curve
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A Si l h t if
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A Simple what if Take current demand, current activity, current
technology, current deployment At a crude top-level scale (by category)
Represented by the time series Scale up the renewable portions
Preserve the seasonal, weekly, daily, hourly effectsof mother nature *
Scale back the fossil fuel based supplies With current demand as a reference
11/7/201267
E ample: Solar
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Example: Solar
11/7/201268
Example: Solar Scaled
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Example: Solar Scaled
11/7/201269
Example: Wind
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Example: Wind
11/7/201270
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A Year in CA grid @ 60%
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A Year in CA grid @ 60%
11/7/201273
Sep Nov Jan Mar May Jul0
10
20
30
40
50
60
70
T o
t a l C A P o w e r
( G W )
EXCESSIMPORTS: 2.6%
THERMAL: 9.7%WIND: 34.4%SOLAR: 18.2%BIOMASS/BIOGAS: 1.9%GEOTHERMAL: 3.8%HYDRO: 13.3%SMALL HYDRO: 1.7%NUCLEAR: 14.5%CA GRID DEMAND
A Summer Week @ 60%
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A Summer Week @ 60%
11/7/201274 Se Nov Jan Mar Ma Jul0
10
20
30
40
50
60
70
T o
t a l C A P o w e r
( G W )
EXCESSIMPORTS: 2.6%THERMAL: 9.7%WIND: 34.4%SOLAR: 18.2%BIOMASS/BIOGAS: 1.9%GEOTHERMAL: 3.8%HYDRO: 13.3%SMALL HYDRO: 1.7%NUCLEAR: 14.5%CA GRID DEMAND
07/08 07/09 07/10 07/11 07/120
10
20
30
40
50
60
70
80
T o t a
l C A P o w e r
( G W )
EXCESS
IMPORTS: 0.0%
THERMAL: 0.0%
WIND: 41.6%
SOLAR: 20.1%
BIOMASS/BIOGAS: 1.8%
GEOTHERMAL: 3.2%
HYDRO: 15.9%
SMALL HYDRO: 1.9%
NUCLEAR: 15.4%
CA GRID DEMAND
A Winter Week @ 60%
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A Winter Week @ 60%
11/7/201275 Se Nov Jan Mar Ma Jul0
10
20
30
40
50
60
70
T o
t a l C A P o w e r
( G W )
EXCESSIMPORTS: 2.6%THERMAL: 9.7%WIND: 34.4%SOLAR: 18.2%BIOMASS/BIOGAS: 1.9%GEOTHERMAL: 3.8%HYDRO: 13.3%SMALL HYDRO: 1.7%NUCLEAR: 14.5%CA GRID DEMAND
12/19 12/20 12/21 12/22 12/230
10
20
30
40
50
60
70
80
T o
t a l C A
P o w e r
( G W )
EXCESS
IMPORTS: 1.8%
THERMAL: 22.9%
WIND: 33.4%
SOLAR: 6.8%BIOMASS/BIOGAS: 1.9%
GEOTHERMAL: 4.0%
HYDRO: 14.8%
SMALL HYDRO: 1.4%
NUCLEAR: 13.1%
CA GRID DEMAND
CA Grid @ 60%
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CA Grid @ 60%
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What Can we do to Make it Work?
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What Can we do to Make it Work? Design for deep penetration
Optimize for the whole, not peak production Use your off-grid intuition
Efficiency for shaping Poor power proportionality of buildings and other loads,
especially at night Storage
Move energy in time Load scheduling (continuous DR)
Precooling, preheating, guardband adjustment
Deferral, acceleration Integrated Portfolio Management Utilize resources in concert with non-dispatcables
Curtailment
11/7/201277
Load shifting to follow supply
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Load shifting to follow supply
11/7/201278
Sep Nov Jan Mar May Jul0
10
20
30
40
50
60
70
T o
t a l C A P o w e r
( G W )
EXCESSIMPORTS: 2.6%
THERMAL: 9.7%WIND: 34.4%SOLAR: 18.2%BIOMASS/BIOGAS: 1.9%GEOTHERMAL: 3.8%HYDRO: 13.3%SMALL HYDRO: 1.7%NUCLEAR: 14.5%CA GRID DEMAND
Windrush?Sunrush?- energy agile
industry?
A Day
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A Day
00:00 06:00 12:00 18:000
5
10
15
20
25
30
35
T o
t a l C A P o w e r
( G W )
EXCESS
IMPORTS: 1.0%
THERMAL: 21.2%
WIND: 33.9%
SOLAR: 15.8%
BIOMASS/BIOGAS: 2.1%
GEOTHERMAL: 4.2%
HYDRO: 10.8%
SMALL HYDRO: 1.3%
NUCLEAR: 9.8%
CA GRID DEMAND
11/7/201279
The Day with +/- 3 hours of shift
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The Day with +/- 3 hours of shift
00:00 06:00 12:00 18:000
5
10
15
20
25
30
35
T o
t a l C A P o w e r
( G W )
EXCESS
IMPORTS: 0.6%THERMAL: 16.4%
WIND: 35.7%
SOLAR: 19.1%
BIOMASS/BIOGAS: 2.1%
GEOTHERMAL: 4.2%
HYDRO: 10.8%
SMALL HYDRO: 1.3%
NUCLEAR: 9.8%
CA GRID DEMAND
11/7/201280
How to match demand to supply?
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How to match demand to supply?
11/7/201281
Modern EE & CS Energy Challenges
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gy g
Supply Transport ConsumptionLoad
Generators Lines
TransformersMeters
VFDEfficiency
Usage
ScheduleControl
Pricing
Baseline
Intermittent
Peaker
FluctuatingRenewable
Nuclear ,Coal
HydroGeothermal
Combined cyclenat. gas / bio
Single cyclenat. gas /
bio
PhotovoltaicWind
T r a n s m
i s s i o n
D i s t r i b u t i o n
Imports
Motors
Lighting
HVAC
Electronics
ApplianceFacilities
Personal
Industrial
Transportation
Power Supplies
FluctuatingRenewable
Storage Storage Storage Pumped
Information Plane
Physical PlaneCircuits
11/7/201282
Interesting Sensor Networks
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g151 Temperature Sensors
50 Electrical Sub-meters
12 Variable Speed Fans
138 Air Dampers
312 Light Relays
6 Variable Speed Pumps
121 Controllable Valves
> 6 , 0 0 0 S e n s e a n d
C o n t r o l P o i n t s
Sutardja Dai HallBuilt in 2009
140k sq. ft.11/7/201283
Controls are Widely Available
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Controls are Widely Available
Bancroft Library: Built in 1949 100k sq. ft.
5,000 points
>70% of large buildings have digital controls
U.S. Energy Information Administration, 2009 11/7/201284
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Measure => Model => Mitigate
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Mathematical model from Newtons law of cooling
Model identied using semi-parametric regression
dT/dt = -k r T - k cu(t) + k ww(t) ) + q(t)change in temperature
over time
time constantof room
AC cooling
weather heating from occupantsand equipment
11AM 12PM 1PM 2PM 3PM 4PM 5PM 6PM 7PM 8PM
21
22
23
Time
( C )
11AM 12PM 1PM 2PM 3PM 4PM 5PM 6PM 7PM 8PM
0.0285
0.029
( C / s )
Time
Temperature:Experimental (blue)Simulated (red)
Heating from occupantsand equipment
11/7/201286
Learning-Based Model Predictive Control
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1PM 3PM 5PM 7PM 9PM 11PM 1AM 3AM 5AM 7AM 9AM 11AM
22
23
Time
( C )
1PM 3PM 5PM 7PM 9PM 11PM 1AM 3AM 5AM 7AM 9AM 11AM
0
1
A C
S t a t e
Time
1PM 3PM 5PM 7PM 9PM 11PM 1AM 3AM 5AM 7AM 9AM 11AM
22
23
( C )
Time
1PM 3PM 5PM 7PM 9PM 11PM 1AM 3AM 5AM 7AM 9AM 11AM
0
1
A C
S t a t e
Time
Experimental LBMPC: 12.6kWh Consumed
Temperature
Control Action
Simulated Hysteresis Control: 29.7kWh Consumed (estimated)
Temperature
Control Action
(Aswani, Master, Taneja, Culler, Tomlin, 2011)
g
LBMPC adjusts for internal dynamics, avoids over-cooling, trades off duty cycle and switching frequency
0 2 4 6 80
1
2
3
4
5
6
Minutes
k W
Transient PowerSteady State Power
11/7/201287
Supply-Following Computational
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Supply Following ComputationalLoads
11/7/201288
IPSRequests
Power
Background Processing (shiftable)
Controllable Storage
QoS (fidelity & latency)
Availability
Forecasts
Energy-Availability Driven Scheduling
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Non-dispatchable,variable supply
Power proportional,grid-aware loads
NREL Western Wind and Solar Integration Study Datasethttp://wind.nrel.gov/Web_nrel/
0 200 400 600 8000
2
4
6
8
10
12
14 x 104
Time (hrs)
P o w e r ( W )
Pacheco wind farm
0 200 400 600 8000
1
2
3
4
5
x 104
Time (hrs)
P o w
e r ( W )
Scientific computingcluster
200 250 3000
1
2
3
4
5
x 104 greedy pacheco 2.0x
Time (hrs)
P o w
e r ( W )
11/7/201289
Energy Slack
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gy
90
ThermostaticallyControlled Load
Set Point
IPSGuard band
11/7/2012
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From Auto Demand Response
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11/7/201292
Sutardja Dai Hall
To Personalized Automated Lighting
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Control
Three controllableballasts per xture
~5 zones per oor
BACnetsMAP
HTTP
Gateway
MySQLPythonDjango
PythonControlProcess
11/7/201293
Real Energy Savings
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11/7/201294
0 0
58%
68% 69%63%
53%
65%68%
75%71%
61%
0%
10%
20%
30%
40%
50%
60%
70%
80%
0
0.5
1
1.5
2
2.5
3
3.5
4
K W
SDH 4th Floor Lighting Energy Usage
Colab Savings
Floor kW
Collab kW
A Macroscope ???
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10/11 00:00 10/11 12:00 10/12 00:00 10/12 12:00 10/13 00:00 10/13 12:00100
80
60
40
20
0
20
40
60
80
100
100% Cooling
100% Heating
Dead band
11/7/201295
Network of
Cooling Tower Loop
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Dampers(VAVs)
Heating Coils &Valves
70 F setpoint
Condenser Water Pump (CWP)Always on max
Control
Loops
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Outside Air Intake
Supply Fan(Air Handler Unit AHU)
336 Pa setpoint
Exhaust Air Return Fan
Cooling Coil & Valve55 F setpoint
Chilled Water Pump (CHP)Always on max
Chiller 45 F setpoint
Cold Water Loop
H o t W
a t e r
L o o p
V A V L o o p
V A V L o o p
V A V L o o p
Air Handling
Loop
E c o n o m
i z e r
L o o p
Script the building
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11/7/201297
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11/7/201298
Theres a bldg app for that
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g pp
11/7/201299
Holistic HVAC optimization
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11/7/2012100
12/10 12/11 12/12 12/13 12/14 12/15 12/16 12/17 12/18 12/19120
140
160
180
200
220
240
260
280
RMSE = 5.6%
Savings: 16.52%25.4 kW
P o w e r ( k W )
MeasuredBaseline
Empirical models, includingexternal factors, and
monitoring, provide rapid,focused feedback
Dynamically set economizer, supply air temp, minairow, reheat
0 8/10 0 8/10 0 8/11 0 8/11 0 8/12 0 8/12 0 8/13 0 8/13 0 8/14 0 8/140
2
4
6
8
10x 10
4
A i r F l o w
( C F M )
Fresh air
Return Air
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CyberPhysical Building Systems
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BMS
Cyber Physical Building
L i g h
t
T r a n s p o r tProcess
Loads
Occupan tDemand
LegacyInstrumentation &Control Interfaces
PervasiveSensing
Activity/Usage
Streams
Local Controllers
Planning Visualiza;on
OccupantSa;sfac;on
Mul;-Objec;veModel-Driven
Control
Building IntegratedOperating System
H V A C
E l e c t r i c a
l
S e c u r i
t y , F
a u l t
, A n o m a l y
D e t e c t
& M a n a g e m e n
t
Control andScheduleExternal
Physical
Models
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BIM
EmpiricalModels
drvrs drvrs drvrs
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Synchrophasors
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Synchronized Phasor Measurement Units (PMUs)
distributed across the transmission system 30 Hz sampling of voltage, current, frequency & phase Synchronized (
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Power Systems Applications Enhanced state estimation, Operator visualization Black Start visibility, Line impedance derivation Oscillatory mode detection & damping Post-disturbance analysis, Islanding Power network model validation
11/7/2012105
Phase Difference beforethe Blackout
Aug 14, 2003
Currently ~500 PMUs in US grid
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y g
11/7/2012106
The issues to solve?
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Sensor placement Huge complex grid, few expensive PMUs
Time synchronization Higher delity requires tighter synchronization Especially as we move to the distribution tier
Latency Data rates (!), storage, query Continuous, unattended operation
Especially during crises Analytics, Prognostics,
11/7/2012107
DIY Synchrophasors
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11/7/2012108
What happens when ?
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Push observability throughout distribution tier? Into consumption tier ? Electrify more and more of the transportation ? The loads become efficient, power
proportional, and grid responsive?
11/7/2012109
From a Grid to an Energy Network
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110
Load IPS
SourceIPS
energysubnet
IntelligentPower Switch
Monitor, Model, Mitigate
Deep instrumentation Waste elimination Efficient Operation
Shifting, Scheduling, Adaptation
Forecasting Tracking Market
Availability Pricing Planning
11/7/2012
IT and the 4 Part GHG
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Reduction Plan
Efficiency
Electrify Decarbonize
the electricity Decarbonize
the fuel
111
Monitoring, Analysis, Modeling,Waste Elimination, Power
Proportionality, Optimal Control
Intelligence, Communication,adaptation in Everything
ZELB. Supply-Following Loads,Energy SLA, Cooperative Grid
11/7/2012
What made me think it was time for
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WSN reseatch?
11/7/2012112
Why the next tier of internet is here?
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11/7/2012113
Thanks
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