Invited Speakers
Peter W. Sauer, Grainger Chair Professor, Electrical and Computer Engineering, University of Illinois at Urbana-Champaign
Keynote: "Data and metrics for power grids and energy supply sustainability"
The emergence of the smart grid and machine learning as two strong topics has led to numerous applications that directly help the sustainability of the power grid and the energy sources. This talk will present fundamental issues and opportunities for Direct Data Driven Applications as well as Data Analytics for energy delivery systems. This will include the challenges of full utilization of renewable resources, customer interaction, energy markets, and optimal strategies. One focus will be on exploiting the vast supply of Phasor Measurement Units (PMUs) and the potential for model-less analysis and control.
Pete Sauer is the Grainger Chair Professor of Electrical Engineering at Illinois. He received his MS and Ph.D. degrees in Electrical Engineering from Purdue University in 1974 and 1977 respectively. He has been on the faculty at The University of Illinois at Urbana-Champaign since 1977 where he teaches courses and directs research on power systems and electric machines. His main contributions are in modeling and simulation of power system dynamics with applications to steady-state and transient stability analysis. From August 1991 to August 1992 Pete served as the Program Director for Power Systems in the Electrical and Communication Systems Division of the National Science Foundation in Washington D.C. He retired from the Air Force reserves as a Lt. Col. in 1998. He was a cofounder and chairman of PowerWorld Corporation, and a cofounder of the Power Systems Engineering Research Center (PSERC) where he served as the Illinois site director from 1996 to 2015. From 2011 to 2015 he served as the Vice President for Education in the IEEE Power and Energy Society. He is a Fellow of the IEEE, and a member of the U.S. National Academy of Engineering.
Keynote: "Data and metrics for power grids and energy supply sustainability"
The emergence of the smart grid and machine learning as two strong topics has led to numerous applications that directly help the sustainability of the power grid and the energy sources. This talk will present fundamental issues and opportunities for Direct Data Driven Applications as well as Data Analytics for energy delivery systems. This will include the challenges of full utilization of renewable resources, customer interaction, energy markets, and optimal strategies. One focus will be on exploiting the vast supply of Phasor Measurement Units (PMUs) and the potential for model-less analysis and control.
Pete Sauer is the Grainger Chair Professor of Electrical Engineering at Illinois. He received his MS and Ph.D. degrees in Electrical Engineering from Purdue University in 1974 and 1977 respectively. He has been on the faculty at The University of Illinois at Urbana-Champaign since 1977 where he teaches courses and directs research on power systems and electric machines. His main contributions are in modeling and simulation of power system dynamics with applications to steady-state and transient stability analysis. From August 1991 to August 1992 Pete served as the Program Director for Power Systems in the Electrical and Communication Systems Division of the National Science Foundation in Washington D.C. He retired from the Air Force reserves as a Lt. Col. in 1998. He was a cofounder and chairman of PowerWorld Corporation, and a cofounder of the Power Systems Engineering Research Center (PSERC) where he served as the Illinois site director from 1996 to 2015. From 2011 to 2015 he served as the Vice President for Education in the IEEE Power and Energy Society. He is a Fellow of the IEEE, and a member of the U.S. National Academy of Engineering.
David Irwin, Assistant Professor, Electrical and Computer Engineering, University of Massachusetts Amherst
Keynote: "Staring at the Sun: Solar Energy Analytics and their Privacy Implications"
The penetration of solar energy in the grid is rising rapidly due to continuing declines in solar module prices. However, large-scale solar penetration imposes an increasing burden on the grid to absorb a consumers' solar energy surpluses and make up for their energy deficits. The energy produced by solar deployments is often monitored directly or indirectly by utilities and third parties using networked energy meters, which record and transmit energy data at fine-grained intervals. While this solar energy data is a rich source of information that can improve grid operations, it also has serious privacy implications. In this talk, we present some recent work on solar energy analytics that illustrates this dichotomy. We first present SunDance, a technique for disaggregating solar power from a building's net energy usage. Since the vast majority of solar deployments are "behind the meter," accurate solar disaggregation can significantly improve utilities' visibility into distributed solar generation. Unfortunately, solar energy data is not anonymous: since every location on Earth has a unique solar signature, it embeds detailed location information. To explore the severity and extent of this privacy threat, we present SunSpot, a technique for localizing "anonymous" solar-powered buildings from their solar energy data.
David Irwin is an Assistant Professor in the Electrical and Computer Engineering Department at the University of Massachusetts Amherst where he leads the Sustainable Computing Lab. His research focuses on designing, building, and analyzing experimental software systems with a particular emphasis on improving sustainability. This research cuts across multiple areas, including operating systems and virtualization, distributed systems and networking, embedded sensor systems, data analytics, security and privacy, and economics. He is the recipient of a NSF CAREER award and Google Faculty Research award. In addition, his HPDC '03 paper was recently selected as #4 of the twenty best papers to appear in the conference's first 20 years.
Keynote: "Staring at the Sun: Solar Energy Analytics and their Privacy Implications"
The penetration of solar energy in the grid is rising rapidly due to continuing declines in solar module prices. However, large-scale solar penetration imposes an increasing burden on the grid to absorb a consumers' solar energy surpluses and make up for their energy deficits. The energy produced by solar deployments is often monitored directly or indirectly by utilities and third parties using networked energy meters, which record and transmit energy data at fine-grained intervals. While this solar energy data is a rich source of information that can improve grid operations, it also has serious privacy implications. In this talk, we present some recent work on solar energy analytics that illustrates this dichotomy. We first present SunDance, a technique for disaggregating solar power from a building's net energy usage. Since the vast majority of solar deployments are "behind the meter," accurate solar disaggregation can significantly improve utilities' visibility into distributed solar generation. Unfortunately, solar energy data is not anonymous: since every location on Earth has a unique solar signature, it embeds detailed location information. To explore the severity and extent of this privacy threat, we present SunSpot, a technique for localizing "anonymous" solar-powered buildings from their solar energy data.
David Irwin is an Assistant Professor in the Electrical and Computer Engineering Department at the University of Massachusetts Amherst where he leads the Sustainable Computing Lab. His research focuses on designing, building, and analyzing experimental software systems with a particular emphasis on improving sustainability. This research cuts across multiple areas, including operating systems and virtualization, distributed systems and networking, embedded sensor systems, data analytics, security and privacy, and economics. He is the recipient of a NSF CAREER award and Google Faculty Research award. In addition, his HPDC '03 paper was recently selected as #4 of the twenty best papers to appear in the conference's first 20 years.
Thomas F. Wenisch, Associate Professor, Electrical Engineering and Computer Science, University of Michigan
Keynote: "Report from the Arch2030 Visioning Workshop: Where are Computer Architects headed and what does it mean for GreenMetrics?"
Last June, the computer architecture community engaged in a public visioning workshop to identify the key challenges in computer architecture research over the next 15 years. This workshop, sponsored by the Computing Research Association's Computing Community Consortium, engaged nearly 150 computer architecture researchers in a series of talks and discussions to determine the central problems the community must solve in light of the impending end of Moore's Law. A key objective of the workshop is to provide guidance to funding agencies to help set priorities for investment. In this talk, I will summarize the outbrief the workshop report co-editors (Luis Ceze, U. Washington; Mark Hill, U. Wisconsin; and myself) deliver to the National Science Foundation and discuss possible implications for the Sigmetrics/Greenmetrics community.
A link to the CCC White Paper reporting the findings from the visioning workshop can be found here.
Thomas Wenisch is an Associate Professor of Computer Science and Engineering at the University of Michigan, specializing in computer architecture. His prior research includes memory streaming for commercial server applications, computational sprinting, multiprocessor memory systems, memory disaggregation, and rigorous sampling-based performance evaluation methodologies. His ongoing work focuses on server and data center architectures, programming models for byte-addressable NVRAM, and architectural support for 3D medical image reconstruction. Wenisch received the NSF CAREER award in 2009. Prior to his academic career, Wenisch was a software developer at American Power Conversion, where he worked on data center thermal topology estimation. He received his Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University.
Keynote: "Report from the Arch2030 Visioning Workshop: Where are Computer Architects headed and what does it mean for GreenMetrics?"
Last June, the computer architecture community engaged in a public visioning workshop to identify the key challenges in computer architecture research over the next 15 years. This workshop, sponsored by the Computing Research Association's Computing Community Consortium, engaged nearly 150 computer architecture researchers in a series of talks and discussions to determine the central problems the community must solve in light of the impending end of Moore's Law. A key objective of the workshop is to provide guidance to funding agencies to help set priorities for investment. In this talk, I will summarize the outbrief the workshop report co-editors (Luis Ceze, U. Washington; Mark Hill, U. Wisconsin; and myself) deliver to the National Science Foundation and discuss possible implications for the Sigmetrics/Greenmetrics community.
A link to the CCC White Paper reporting the findings from the visioning workshop can be found here.
Thomas Wenisch is an Associate Professor of Computer Science and Engineering at the University of Michigan, specializing in computer architecture. His prior research includes memory streaming for commercial server applications, computational sprinting, multiprocessor memory systems, memory disaggregation, and rigorous sampling-based performance evaluation methodologies. His ongoing work focuses on server and data center architectures, programming models for byte-addressable NVRAM, and architectural support for 3D medical image reconstruction. Wenisch received the NSF CAREER award in 2009. Prior to his academic career, Wenisch was a software developer at American Power Conversion, where he worked on data center thermal topology estimation. He received his Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University.
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