LoCal: Rethinking the Energy Infrastructure using Internet Design

Principles

David CullerUniversity of California, Berkeley

Renewable Energy Microgrid Research Workshop June 5, 2009

“Energy permits things to exist; information, to behave purposefully.” W. Ware, 1997

2

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

Towards an Information Age Energy Infrastructure

3

Baseline + Dispatchable Tiers

DistributionTransmissionGeneration Demand

Nearly Oblivious Loads

Non-Dispatchable Sources

Interactive Dispatchable Loads???

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

5

Conventional Electric Grid

Generation

Transmission

Distribution

Load

Intelligent Energy Network

Load IPS

Source IPS

energy subnet

Intelligent Power Switch

Conventional Internet

6

Intelligent Power Switch

(IPS)

Energy Network

PowerComm Interface

EnergyStorage

PowerGeneration

Host Load

Intelligent Power Switch

(IPS)EnergyStorage

Intelligent Power Switch

(IPS)EnergyStorageEnergyStorage

Intelligent Power Switch

(IPS)EnergyStorage

Intelligent Power Switch

(IPS)EnergyStorageEnergyStorage

Intelligent Power Switch

(IPS)EnergyStorage

Intelligent Power Switch

(IPS)EnergyStorageEnergyStorage

Intelligent Power Switch

(IPS)EnergyStorage

Intelligent Power Switch

(IPS)EnergyStorageEnergyStorage

Host LoadHost Load

energy flows

information flows

Intelligent Power Switch

• PowerComm Interface: Network + Power connector• Scale Down, Scale Out

7

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

MultiScale Approach

8

IPScomm

power

now

Load profile

w$

now

Price profile

w

now

Actual load

w

Data centerIPS

Bldg Energy

Network

IPS

IPS

IPSInternet

Grid

IPS

IPS

Power proportional kernel

Power proportional service manager

Quality-Adaptive Service

M/R Energy

Net

IPS

IPS

IPS

AHU

Chill

CT

Start with IT Equipment

9

10

Datacenters

3-19-2004 11

Server Power Consumption

230

15

248

87

190

13

190

13

200

14

161

19

287

48

0

50

100

150

200

250

300

350

Wat

ts

Pow

erE

dge

1850

Del

l Pow

erE

dge

1950

Sun

Fire

V60

x

Sun

Fire

x21

00 -

Cyb

er S

witc

hing

Sun

Fire

X22

00

Com

paq

DL3

60

HP

Int

egrit

y rx

2600

Server Power Consumption

Active

Idle Soda Machine Room Power Consumption

26.5 30.6 31

18.118.9 19

44.5

50.9 50

9.5

10.117

10

31

0

20

40

60

80

100

120

140

160

180

est kW min est kW max kW meas

KW

290 Soda

288 Soda

530 Soda

420A Soda

340 Soda

287 Soda

• x 1/PDU efficiency + ACC

• If Pidle = 0 we’d save ~125 kw x 24 hours x 365 …

• … Do Nothing Well

Understanding Diverse Load

12

ACme – HiFi Metering 13

Energy Consumption Breakdown

14

Re-aggregation

15

By Individual

16

17

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

18

EnergyInterconnect

LocalGeneration

Local Load

IPS

LocalStorage

IPS

IPS

IPS

IPS

IPS

Scaling Energy Cooperation

• Hierarchical aggregates of loads and IPSs• Overlay on existing Energy Grid

Energy InterconnectCommunications Interconnect

19

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

Initial Steps

20

21

“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

3-19-2004 22

Cooperative Continuous Reduction

Automated Control

Facility Mgmt

User Demand

Supervisory Control

Community Feedback

High-fidelity visibility

Questions

23