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An Intel Snapshot Computational Intelligence for Energy, Sustainability & Beyond Eve M. Schooler, Ph.D. Energy and Sustainability Lab, Intel Labs March 1, 2013

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An Intel Snapshot Computational Intelligence for Energy, Sustainability & Beyond

Eve M. Schooler, Ph.D. Energy and Sustainability Lab, Intel Labs

March 1, 2013

Intel's Vision

This decade we will create and extend computing technology to

connect and enrich the lives of every person on earth.

Develop technology solutions to address major global problems while reducing our environmental impact

Questions Posed

• What are Intel's R&D interests/investments in emerging markets and/or in the microgrids space?

• Ideas for collaboration with the university & NGO partners in the DIL consortium?

INTEL PRODUCT

GROUPS

Technology Transfer Strong Research

Partnerships

UNIVERSITIES

GOVERNMENT

INDUSTRY

Intel Labs : Delivering Breakthrough Technologies to Fuel Intel’s Growth

Energy and Sustainability Lab (EU)

IPR/Frugal Innovation Lab (India)

User Experience/Data Economy

University Research Office

Emerging Markets: USAID-Intel Collaboration

• 6 years of Partnership (2006-2012) • e.g., “One World Ahead”

• Original focus: • Education, Connectivity, SME • Original countries: Kenya, Colombia, Vietnam

• Expanded focus in 2012: • Access to Broadband, USAID’s Grand Challenges, Education, Climate Change, Health, Entrepreneurship • New 5-year MOU signed

• Ongoing work in: • Brazil, Egypt, Pakistan, Guatemala, Indonesia, Jordon, Kenya, Malawi, Nigeria, Peru, Phillipines, Senegal, S. Afric, Tanzania

The Impact of (Smart) Phones on Emerging Markets

• In-depth work – India, Indonesia, now Sub-Saharan Africa

• Uganda - No infrastructure, yet abundance of cell phones

– What is data? How is it being used? What happens to the data captured by telecoms and govt?

– Community radio – people’s information structures

– Women and Land Tenure – market places in Kompala

• Kenya - “All data collected should be open”…good? bad?

– Pushing to develop open data portals and data analytics

– Phone w/attachable Camera Array – small itsy bitsy cameras, almost 3-D pics

• S. Africa – Ethnographic study of traders in Johannesburg

– Tracking everyday activities w/ and w/out phones

Microgrid Investments …

Microgrid control with Univ. of Colorado & PGE

• 2010-11 : Developed component and system models in a simulation platform to

support investigations of architectural, control and optimization techniques in

microgrids. (ECCE ‘10)

http://www.pnwsmartgrid.org/

• 2011-12 : Used platform to develop

Energy Mgmt System for a microgrid in

PGE service territory • Part of the Pacific Northwest Smart Grid Demonstration Project

• 2013-14 : Evaluate performance of

algorithms real-time

8

Microgrid simulation tool (Matlab/Simulink/SimPower) “Building” block is the fundamental unit; configure with combination of many common resources

“Control & Weather” block contains algorithms for microgrid-level control and globally loaded data

for weather, electricity price, etc.

“Smart Breaker” detects and opens in the case of grid faults;

resynchronizes and closes when grid is restored

Phasor domain (1 & 3)

External Control

1

Ground

2

Smart Breaker

node 10

node 10

Grid14.4kV

60Hz

Control&WeatherBuilding #4

AC1

AC2

Building #3

AC1

AC2

Building #2

AC1

AC2

Building #1

AC1

AC2

1

2

3

14.4kV:480V

1

2

3

14.4kV:240V

2

AC2

1

AC1

AC1

AC2

Water Heater

AC1

AC2

Passive Loads

AC1

AC2

PV

AC1

AC2

HVAC

HEMS

AC1

AC2

Generator

AC1

AC2

EV

AC1

AC2

Dryer

AC1

AC2

Dishwasher

AC1

AC2

Battery

2

AC2

1

AC1

AC1

AC2

Water Heater

AC1

AC2

Passive Loads

AC1

AC2

PV

AC1

AC2

HVAC

HEMS

AC1

AC2

Generator

AC1

AC2

EV

AC1

AC2

Dryer

AC1

AC2

Dishwasher

AC1

AC2

Battery

External Control

1

Ground

2

Smart Breaker

node 10

node 10

Grid14.4kV

60Hz

Control&WeatherBuilding #4

AC1

AC2

Building #3

AC1

AC2

Building #2

AC1

AC2

Building #1

AC1

AC2

1

2

3

14.4kV:480V

1

2

3

14.4kV:240V

Direct-Current (DC) Microgrids

• The world is already DC

• HVDC transmission

• 80% of power handled by power electronics (DC)1

• Sustainable /Alternate Energy (PV, Wind, Fuel Cells)

• Energy Storage (Batteries)

• Datacenters (ETSI 300 132-3)

• CFCs, LEDs, EVs, VFD Motors

• DC can save 5-30% 2

1 Center for Power Electronics Systems (CPES) 2 EMerge Alliance; For further information: [email protected]

Furnace

AC Outdoor

Unit Hot Water

Gas Fireplace

Range Dryer

Washing Machine

Refrigerator

TV & Cable Box

Home PC

Thermostat Energy Storage

Solar PV

DC distribution for Lighting, buildings and IT

380VDC – The New Standard

ETSI 300132-3 (draft), EMerge Alliance

4-7% more efficient than AC1,2

15% less up-front capital cost in volume2

33% less floor space2

36% lower lifetime cost3

200%-1000% more reliable2

No Harmonics

11

380VDC To Class II Touch-safe 24VDC in ceiling rails for high-efficiency office lighting

Rack

208V AC

Server PSU

UPS

12V 380-

410V

DC DC/DC

AC/DC DC/AC

PDU

VR AC/DC

Bypass

480V AC MV

Chrg

380VDC: Highest voltage,

volume components, fewest conversions

8/27: UCSD 380VDC Datacenter

1 Intel, Intelec Paper, 2007 2 Intel, HP/EYP, Emerson, Whitepaper, 2009 3 Validus/GE Study, 2010

More Renewables with Micro-Dispatchable Loads – The Smart-Grid can only add

20-30% alternate energy

– Use Cloud Data Centers, as a load

– Balance Power vs. Workload

– Stabilize & firm the output

– Augment Cloud Data Centers with Demand-Response revenue

– Input : solar, wind, price-signal, … CLOUD

DATA CENTER

CONTROLLER

INPUT

SENSORS

SERVER POWER & PERFORMANCE METRICS

WORKLOAD

DISPATCH

SERVICE LEVEL

AGREEMENT (SETPOINT)

PV ENERGY

STORAGE

380VDC

DCM

0

2000

4000

6000

8000

10000

40700.42 40700.52 40700.62 40700.72 40700.82

NM ESRC 10kW PV Array, with 1 minute interval data(June 6th: Clear in Morning but Partially Cloudy in Afternoon)

AC Power (W)

Trendline2

Poly. (Trendline2)

Clouds can

take PV output

to 20% in seconds

Community EV charging PoC

• In conjunction with University College Dublin

• Highly instrumented microgrid

– 74 homes with Smart meters and a variety of smart appliances

– 7 EV’s allocated to trials

• Focus on EV charge control based on network events and price

– Centralized (aggregator) and decentralized control experiments

– Validate behavior prediction accuracy & assess consumer trust

EV optimization and prediction PoC From where you need to go and your journey home

Who you share the road with… to who you share your home with, and how to support you.

SMART Devices / Appliances (Isolated Systems)

SMART People (Using SMART Devices via Semi-connected Systems)

Intelligent Homes (Ubiquitous SMART Devices in a single Semi-connected System)

Intelligent Neighborhoods (SMART Homes all Connected via a System of Systems)

Citizen Centric (Sustainable Interconnected & Secure Economy-Society- Environment)

Intelligent Communities (Mega-SMART, Secure Infrastructures in Interconnected System of Systems)

Sustainable Connected Cities

16

Connected City Infrastructures

Health &

Wellbeing

Transport &

Logistics Energy Systems Pollution & Heat

Island

Water &

Waste Built

Environment Citizens &

Community

Sustainable City Experiences

Ubiquitous Communication

M2M / Distributed

APIs

Intel SoC & Hardware Platform

Se

curity

, Priv

acy

& T

rust

Data Management & Analytics

Pecan Street Inc. - Smart Grid Pilot

Team of researchers from the UT, NREL and EDF collaborate to develop and test an integrated clean energy smart grid of tomorrow in the homes of today.

1100 homes equipped with PV, smart appliances, sensors, some with EVs.

University of Texas Advanced Computing Center (TACC) super computer and advanced visualization

Intel involved since ’09 & on Industry Advisory Board

Environmental Visualization Lab Will visualize results using projection,

tile, touch screen, and motion technologies

Potential Collaboration Ideas

– Sustainable Connected City for the developing world

– Measurement fusion and the impact of data sharing

– Monitoring the Monitoring – 2nd order analytics

– Privacy preservation – data, devices, users

– “Resource” caching and failure resilience as the norm

– Truly autonomous microgrids/nanogrids/picogrids