LoCal: Rethinking the Energy Infrastructure using Internet Design Principles David Culler University of California, Berkeley Renewable Energy Microgrid Research Workshop June 5, 2009 “Energy permits things to.

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Transcript LoCal: Rethinking the Energy Infrastructure using Internet Design Principles David Culler University of California, Berkeley Renewable Energy Microgrid Research Workshop June 5, 2009 “Energy permits things to.

LoCal: Rethinking the Energy
Infrastructure using Internet Design
Principles
David Culler
University of California, Berkeley
Renewable Energy Microgrid Research Workshop
June 5, 2009
“Energy permits things to exist; information, to behave purposefully.”
W. Ware, 1997
What if the Energy Infrastructure
were Designed like the Internet?
• Energy: the limited resource of the 21st Century
• Needed: Information Age approach to the
Machine Age infrastructure
• Match load & supply through continuous observation and
adjustment
• Lower cost, more incremental deployment, able to
accommodate technology innovation
• Enhanced reliability and resilience through intelligence at
the edges
– Dumb grid, smart loads and supplies
• Packetized Energy: discrete units of energy locally
generated, stored, and forwarded to where it is needed;
enabling a market for energy exchange
2
Towards an Information Age
Energy Infrastructure
Baseline + Dispatchable Tiers
Generation
Transmission
Nearly Oblivious Loads
Distribution
Demand
Non-Dispatchable Sources
Interactive Dispatchable Loads
???
3
Energy Network Architecture
• Information exchanged whenever energy
is transferred
• Loads are “Aware” and sculptable
– Forecast demand, adjust according to
availability / price, self-moderate
• Supplies negotiate with loads
• Storage, local generation, demand
response are intrinsic
4
Information Overlay to the
Energy Grid
Intelligent Energy Network
Source
IPS
energy
subnet
Load IPS
Intelligent
Power Switch
Generation
Transmission
Distribution
Load
Conventional Electric Grid
Conventional Internet
5
Intelligent Power Switch
Host Load
Intelligent
Power Switch
(IPS)
Intelligent
Power Switch
(IPS)
Power
Generation
Host Load
Energy
Storage
Energy
Storage
energy flows
PowerComm
Interface
Intelligent
Power Switch
(IPS)
Energy
Storage
Intelligent
Power Switch
(IPS)
Energy Network
information flows
Intelligent
Power Switch
(IPS)
Energy
Storage
Energy
Storage
• PowerComm Interface: Network + Power connector
• Scale Down, Scale Out
6
Intelligent Power Switch
• Interconnects load to power sharing infrastructure
• Bundles communications with energy
interconnection -- PowerComm interface
• Enables intelligent energy exchange
• Optionally incorporates energy generation and
buffering
– Potential to scale-down to individual loads, e.g., light
bulb, refrigerator
– Scale-up to neighborhoods, regions, etc.
• Overlay on the existing power grid
7
MultiScale Approach
Price profile
w
Load profile
w
$
IPS
CT
now
now
IPS
comm
Internet
Bldg
IPS Energy
Network
power
IPS
Grid
AHU
IPS
Actual load
IPS
Data center
IPS
IPS
Chill
w
Power
proportional
kernel
IPS
M/R
Energy
Net IPS
now
Power
proportional
service
manager
QualityAdaptive
Service
8
Start with IT Equipment
9
Datacenters
10
Server Power Consumption
Server Power Consumption
350
48
Active
87
300
Soda Machine Room Power Consumption
Idle
Watts
250
15
180
13
200
13
14
160
19
287
150
230
140
31
120
10
248
190
100
190
200
161
10.1
17
9.5
KW
50
HP Integrity rx2600
Compaq DL360
SunFire X2200
SunFire x2100 Cyber Switching
SunFire V60x
Dell PowerEdge
1950
PowerEdge 1850
530 Soda
420A Soda
80
0
290 Soda
288 Soda
100
50.9
50
340 Soda
287 Soda
44.5
60
40
18.1
20
26.5
18.9
19
30.6
31
0
• x 1/PDU efficiency + ACC
• If Pidle = 0 we’d save ~125 kw x 24 hours x 365 …
•
… Do Nothing Well
3-19-2004
est kW min
est kW max
kW meas
11
Understanding Diverse Load
12
ACme – HiFi Metering
13
Energy Consumption
Breakdown
14
Re-aggregation
15
By Individual
16
Energy Aware / Adapt
•
•
•
•
•
•
Export existing facilities instrumentation into
real-time feed and archival physical
information base
Augment with extensive usage-focused
sensing
Create highly visible consumer feedback and
remediation guidance
Develop whole-building dynamic models
Basis for forecasting
And for load sculpting
17
Scaling Energy Cooperation
Local
Storage
IPS
IPS
Energy
Interconnect
IPS
Local
Generation
IPS
IPS
IPS
Local Load
Energy Interconnect
Communications Interconnect
• Hierarchical aggregates of loads and IPSs
18
• Overlay on existing Energy Grid
Enabling Energy Markets
• Information-enabled markets
– Bilateral exchange  multi-lateral exchange 
general markets
• Aggregated load and supply models,
parameterized by time and increasing uncertainty
– Machine learning techniques
• More degrees of freedom:
– (Over) loads can be reduced
– (Over) supplies can be stored
• Match supply to load
– Optimization algorithms vs. auction mechanisms
19
Initial Steps
20
“Doing Nothing Well”
• Existing systems sized for peak and designed for
continuous activity
– Reclaim the idle waste
– Exploit huge gap in peak-to-average power consumption
• Continuous demand response
– Challenge “always on” assumption
– Realize potential of energy-proportionality
• From IT Equipment …
– Better fine-grained idling, faster power
shutdown/restoration
– Pervasive support in operating systems and applications
• … to the OS for the Building
• … to the Grid
21
Cooperative Continuous
Reduction
User Demand
Facility Mgmt
High-fidelity
visibility
Automated Control
Supervisory Control
Community Feedback
3-19-2004
22
Questions
23