LoCal Retreat Winter 2010 Eric Brewer, David Culler, Randy Katz, Seth Sanders EECS Department University of California, Berkeley, CA

Presentation Outline Retreat Purpose and Agenda What is LoCal? Summary and Conclusions

Retreat Goals & Technology Transfer UC Berkeley Project Team Industrial Collaborators Government Sponsors Friends People Project Status Work in Progress Prototype Technology Early Access to Technology Promising Directions Reality Check Feedback

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 – 1130 Travel from Berkeley to Granlibbakkan Lunch LoCal Introduction and Overview, Randy Opportunities and Challenges, David Break 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 Poster Previews 1800 – 1930Dinner (Organized around discussion topics) 1930 – 2100Poster Session

Retreat Schedule Thursday, January 14: Breakfast 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 Break New Ideas in Storage and the Grid Fly Wheel Storage: Seth Stirling Engine Storage: Mike AC/DC Conversion: Evan Lunch/Ski Break Dinner Energy in the Developing World: Eric Brewer Industry Panel Discussion Paths to Innovation and Impact

Retreat Schedule Friday, January 15: Breakfast Modeling, Analysis and Understanding Metering/Measurement as Simple Web-services: Stephen, Fred Towards Slack Analysis: Jay, Prabal Energy Efficient MapReduce: Yanpei Break & Check-out Feedback Session Lunch 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, grids 11

12 Generation Transmission Distribution Machine Age Energy Infrastructure

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 Utility Large-scale industrialization of computing Energy Efficient Computing Embedded Intelligence in Civilian Infrastructures

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 Energy Storage Power Generation Host 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 Network IPS Internet Grid IPS Power proportional kernel Power proportional service manager Quality- Adaptive Service M/R Energy Net 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

Increasing the Effectiveness of Non-Dispatchable Supply

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

Smart Buildings 25 Servers / Clusters HVAC / CRU / PDU support Lighting HVAC & Plug Loads

Instrumented Buildings

Building OS and Evolving Information Model

Slack and Non-Dispatchable Sources Non-dispatchable sources can exhibit a high degree of variability “Slack” is a measure of this variability that we can quantify over a unit of time Loads also exhibit Slack, we can use it to express 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

CS 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

31 Summary and Conclusions LoCal: a scalable energy network –Inherent inefficiencies at all levels of electrical energy distribution –Integrated energy generation and storage –IPS and PowerComm Interface –Energy matching at small, medium, large scale Datacenters  Buildings  Grid