LoCal RetreatWinter 2010
Eric Brewer, David Culler, Randy Katz, Seth Sanders
EECS Department
University of California, Berkeley, CA 94720-1776
Retreat Goals &Technology Transfer
UC Berkeley Project Team Industrial CollaboratorsGovernment Sponsors
Friends
PeopleProject Status
Work in ProgressPrototype Technology
Early Access to TechnologyPromising Directions
Reality CheckFeedback
Retreat Purpose
• First LoCal retreat away from Berkeley
• Early stage where industrial input is critical!– Lots of discussion on the “Smart Grid”– Where is the real opportunity for impact?
• Review initial progress
• Posters, breakouts over dinner, panel
Who is Here?
• Industrial– ArchRock
– Cisco
– Fujitsu Labs USA
– Intel
– Microsoft
– National Semiconductor
– People Power
– PG&E
– QualComm
– Samsung Electronics
– Siemens
• Government/Labs– LBNL
– ORNL
– Innovation Center Denmark
• Academic– University of California, Berkeley
– University of Michigan, Ann Arbor
Retreat Schedule
• Wednesday, January 130730 – 1130 Travel from Berkeley to
Granlibbakkan
1200 - 1330 Lunch
1330 - 1500 LoCal Introduction and Overview, RandyOpportunities and Challenges, David
1500 - 1530 Break
1530 - 1700 Redesigning the Datacenter from the Green Up
Power-Proportional Web Farm : Andrew, Laura, Sara
Power-Proportional Switch Design: David, Ganesh
Power-Proportional HPC Platform: Prashanth, Himanshu
1700 - 1715 Poster Previews
1800 – 1930 Dinner (Organized around discussion topics)
1930 – 2100 Poster Session
Retreat Schedule
• Thursday, January 14:0730 - 0830 Breakfast
0830 - 1000 Building Scale Monitoring and Modeling
Cory Hall CEC Bldg-to-grid Testbed: Fred, Jorge, Ken
First Cut at a Physical Information Bus: Jorge
Learning from Whole-Building Data: Sam, Omar
1000 - 1030 Break
1030 - 1200 New Ideas in Storage and the Grid
Fly Wheel Storage: Seth
Stirling Engine Storage: Mike
AC/DC Conversion: Evan
1200 - 1800 Lunch/Ski Break
1800 - 1930 DinnerEnergy in the Developing World: Eric Brewer
1930 - 2100 Industry Panel Discussion
Paths to Innovation and Impact
Retreat Schedule
• Friday, January 15:0730 - 0830 Breakfast
0830 - 1000 Modeling, Analysis and Understanding
Metering/Measurement as Simple Web-services: Stephen, Fred
Towards Slack Analysis: Jay, Prabal
Energy Efficient MapReduce: Yanpei
1000 - 1030 Break & Check-out
1030 - 1200 Feedback Session
1200 - 1300 Lunch
1300 - Depart Granlibakkan
Breakout Topics
• Closing the User Loop• Sculptability• Drivers and Barriers• Cost vs. Karma• Technology Game Changers• Economics/Policies vs. Technology• Grid Stability• Appropriate Grid Abstractions• Defining Success• Energy Utility Markets• LoCal Security
9
Posters
• Energy Efficient Platform-tools and tradeoffs: Steve, Andrew• Modeling and Mitigating Energy Demands of Hadoop Jobs:
Yanpei• ACme: Fine-Grain Building Energy Monitoring: Fred• IS4-Integrated Sensor-Stream Storage System: Jorge• Personal Energy Visualization & Feedback: Sushant, Jeff• Energy Market Simulator: Mike/Fred/Evan• Wind Project: Ken• LoCluster Design: Sara, Laura, Andrew• Application Protocol for Veris E30 Panel-board Monitoring
System: Jaein and Prashanth
10
What is LoCal?
• Boosting the IQ of the Smart Grid: Information-centric Energy Infrastructure– “Energy permits things to exist; information, to
behave purposefully.” W. Ware, 1997– Concept of Energy Networks: bits follow
where current flows– Pervasive information: monitor, model,
manage– Multiscale aggregates: nodes, racks,
buildings, grids11
Characteristics of the Grid
• Topology– Long distance transmission– Unidirectional distribution
• Coupling– Dispatchable supply and oblivious loads– Supply-to-load synchronization
• Managing Load Uncertainties– Baseload + Intermediate + Peaking Plants– Minimize outages
13
The Big Switch: Clouds + Smart Grids
14
Computing as a Utility
Computing in the UtilityLarge-scale industrializationof computing
EnergyEfficient
Computing
EmbeddedIntelligence in
CivilianInfrastructures
Energy + Information Flow =Third Industrial Revolution
“The coming together of distributed communication technologies and distributed renewable energies via an open access, intelligent power grid, represents “power to the people”. For a younger generation that’s growing up in a less hierarchical and more networked world, the ability to produce and share their own energy, like they produce and share their own information, in an open access intergrid, will seem both natural and commonplace.”
15
Jeremy Rifkin
16
What if the Energy Infrastructure were Designed like the Internet?
• Energy: the limited resource of the 21st Century• Information Age approach: bits follow current flow
– Break synchronization between sources and loads: energy storage/buffering is key
– Lower cost, more incremental deployment, suitable for developing economies
– Enhanced reliability and resilience to wide-area outages, such as after natural disasters
• Exploit information to match sources to loads, manage buffers, integrate renewables, signal demand response, and take advantage of locality
Information Overlay to the Energy Grid
17
Conventional Electric Grid
Generation
Transmission
Distribution
Load
Intelligent Energy Network
Load IPS
Source IPS
energy subnet
Intelligent Power Switch
Conventional Internet
Aware Co-operative Grid
18
• Monitor, Model, Manage• Deep instrumentation• Waste elimination• Efficient Operation
• Shifting, Scheduling, Adaptation
• Forecasting• Tracking• Market
• Availability• Pricing• Planning
19
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
Multi-Scale Energy Internet
20
comm
power
now
Load profile
w$
now
Price profile
w
now
Actual load
w
Datacenter
Bldg Energy
NetworkIPS
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
IPS
LoCal Energy Network
• Investigation of Internet DCs as a design instance of a LoCal Energy Network– “Doing Nothing Well”: Better processing and network
node designs that exhibit more agile transitions into lower energy states during idle times
– Scheduling: identify workloads time shifted to use fewer resources at higher/more efficient levels of utilization
– (Energy) Storage: decoupling production from usage, thus shifting activity in time
– Building-Machine Room Co-Design: Co-management of building facilities (e.g., power, cooling) given usage patterns
LoCal Energy Network Methodology
• Workload modeling and scheduling– When: peak shifting/filling
valleys of processing load– Where: energy implications
of topology, replicas, multi-DC distribution
• Low power processing and network platform– Processing: Agility in entering
low power states when idle– Facility: Couple cooling with
predicted DC peaks, e.g., in advance of need
• Doing Nothing Well
• Scheduling
• Storage
Tools and Techniques
Scheduling
Forecasting Supply
Shifting
Prioritizing
Storage
Monitoring
Modeling
Mitigation/Reduction
Consumption
Slack and Non-Dispatchable Sources
Non-dispatchable sources can exhibit a high degree of variability
“Slack” is a measure of thisvariability that we can quantify over a unit of time
Loads also exhibit Slack, we can use it toexpress the accepted degree of variability
Real-time measurement and communications allow the Slack in a source to be best matched with that available in a load
LoCal Testbeds
• Loads (with storage/supply/transport)– LoCalized Rack– LoCalized Machine Room/Datacenter– LoCalized Building– LoCalized Buildings/Campus/Local Grid
• Storage/Supplies– LoCalized Energy Storage– LoCalized Renewable Energy Source
• Beyond– Standalone Testbed (aka “Burning Man”)
29
CS294-49 Fall 2009
• “Creating the Grid OS: A Computing Systems Approach to Energy Problems”– Physical Layer: Power Systems– Device Layer: Loads (Datacenters and
Buildings)– Information Flows and Protocols– Resource Allocation and Control– System Architecture– Projects
30
Top Related