Clouds Set to Make Smart Grids Smarter

By Nicole Hemsoth

March 21, 2011

The United Nations estimates that in 2009, the world’s population was officially evenly split between rural and urban areas. However, this figure is not a static one—the organization contends that by 2050, almost 70 percent of the projected 9.1 people living on the planet will be living in cities.

Leaving aside the multiple matters tied to population growth in general, if the urban migration figures are correct, cities are going to have to find far more sustainable ways to power their cities—a matter that can be addressed by streamlining, and in some cases reconstructing, IT infrastructure.

A recent report by Microsoft, called “The Central Role of Cloud Computing in Making Cities Energy-Smart” examined the pending urban population push with a focus on refining city energy infrastructure. The authors claim that in order for cities to thrive in the wake of population explosions, they will “need to radically evolve their infrastructures.” This includes water, waste and other crucial systems, but as the report notes, it is “the evolution of energy infrastructure, in particular, that presents an important opportunity to make major reductions in GHG emissions, support economic development and maintain high quality of life in our cities.”

While at one time energy might have only meant power stations and the way electricity was served, the tide is changing. Now, instead of buildings (and a growing range of other structures and devices) being simply consumers of electricity, they are also producing it and sending it back to the grid.

This give and take relationship in the energy grid goes beyond buildings sending energy as well as consuming it. Newer modes of power generation and consumption like electric vehicles which consume power but also use their battery stores to send power back to the grid are on the horizon as are a number of other renewable systems to send and receive energy.

The problem now is to architect a system that takes these logistical problems of the smart grid and manages the complexity efficiently and in a manner that actually enhances power generation and dispersal. In other words, the time has come to turn those massive, power-chugging cloud data centers into the sources of more streamlined, efficient energy use and distribution—forcing them into their own sort of “give and take” relationship.

Maximizing the Power of Smart Grids

Today IBM and British Cable and Wireless announced that they were collaborating on a cloud computing system to monitor the use of power in over 50 million homes via their smart meters. The project, called the “UK Smart Energy Cloud” will “gather data many times a day from smart meters around the country and store it in a cloud hosted within the country. This data then will be sent to power utilities for analysis to aid in better planning for peak loads.

Smart meters have emerged to let utility companies will be more proficient in gauging demand, thus allowing them to plan ahead to prevent outages. While there are other potential benefits for smart meters, including the ability for customers to see when their electricity is cheapest, the goal to maximize energy use is paramount—both for consumers and power companies.

For true revolutionizing of energy infrastructure, however, it will take a great deal more IT horsepower since smart metering alone cannot provide the efficiency required for the big urban boom.  A more integrated approach using information accessible anywhere via cloud-based platforms is needed. This is especially important because the nature of power operations is changing with far more “give back” via wind and other generation mechanisms that allow consumers to shift to providers.

There is no easy task in this mission to build sustainable IT infrastructures, according to Chris Johnston from the Network-Ready device unit at AT&T. He states that “Ultimately, the grid may be transformed into a wirelessly-controlled, digital network capable of handling complex, multi-directional flows of power. Communications and computing must be both cost effective and easy to install.  These criteria greatly favor wireless communications and cloud computing. Companies capable of delivering the necessary wireless communications and cloud computing functionality must also be armed with outstanding service level agreements and disaster recovery capabilities.”

The Microsoft report also gave a hat tip to this complexity, noting that “the coordination of all of those supply sources is complex and requires significant understanding of where, when and how much power is available to satisfy the energy demands of growing cities. This is of course why the integration of sensors, monitoring equipment, advanced control systems and information technologies to collect this supply-side data and turn it into useful, actionable information is important.”

A Data Market for Energy Efficiency

As more renewable energy sources become more pervasive, bringing with them a need to interact with the grid (versus simply be a consumer of its resources) there will need to be a way to merge these elements into the infrastructure. As the Microsoft report on this issue noted, “optimizing energy efficiency across these interconnected systems at the city level requires the secure and reliable collection of massive amounts of data from sensors, meters and controls embedded within these complex systems.

In Microsoft’s view, cloud computing could be the key to providing a flexible platform to bring together these disparate sensors, meters and measurements so that energy efficiency can be streamlined into one system. They note that “developers will be able to deliver new solutions, such as weather forecasts, energy pricing and traffic conditions.” Along with this is other data that can be particularly useful when culled into the big picture cloud platform. This could include building occupancy, energy performance, manufacturing and other activity and even shipping or distribution schedules.

To help developers focused on building smarter city infrastructures, Microsoft has opened its Windows Azure DataMarket, which the company claims will enable “the discovery, exploration and consumption of data from trusted public domains and commercial data sources such as demographics, health, location-based services, real estate, science, transportation, navigation, weather, finance, etc.”  This market for data also provides visualizations and analytics to help developers “see” the data and its wider implications.

In essence, by providing a complex “mashup” of this data, developers will be to create total systems that are integrated for energy efficiency by use of the vast amount of data pertaining to urban elements that might, at first anyway, appear to have little to do with the grid. In short, “applications and services that leverage such a diverse portfolio of disparate data sets will enable new insights for citizens, governments and utilities on how to manage energy infrastructure in real time.”

The company notes that developers can make use of this data on any platform and can incorporate the data via a common API to mobile, desktop and web-based applications. This centralization of information for energy efficient planning (and beyond, the commercial applications are limited only by imagination—and will likely be the primary use) will allow developers unprecedented ease in terms of creating specific local mashups to aid in effective energy use and distribution.

The report out of Redmond, “IT for Energy Smart Cities” notes that this movement to cull data from a range of source to aid in more efficient energy distribution and use is already taking shape. It notes that ISVs are system integrators are already “taking advantage of high performance and cloud computing platforms to deliver solutions and services that address the needs of this evolving energy infrastructure.” According to Microsoft, many of these ISVs and Sis are already players in the power and grid space and are pulling together pieces of information related to everything from building design and management to transportation systems.

Microsoft claims that the “work to evolve energy smart cities is focusing on these major intersecting infrastructures—power generation and grid, buildings, transportation systems and the security, privacy, reliability and accessibility of the general information backbone that connects them.”

Bringing it all Together

Chris Johnston’s assessment that there are big challenges ahead on a number of fronts shouldn’t be taken lightly. Before the merging of disparate technologies and sources of energy production and consumption some core refinements and modernization measures are needed.

Some groups are addressing such challenges, including a team of researchers out of the University of Pittsburgh’s Swanson School of Engineering. The group recently announced that they have embarked on a long-term mission to integrate more efficient power delivery systems into the expanding American power grid. As a release this week noted, “by employing the same simulation technology used to design and engineer electricity grids, the researchers will model an expanded power grid that delivers electricity from the power plant to our homes and businesses with less infrastructure and a more reliable and efficient flow of electricity.”

This attempt to reconstruct infrastructure would allow for better conservation and also will make it simpler to look to more renewable sources of energy that are generated in remote locations. As one of the lead researchers for the project, Gregory Reed, noted the issue with power delivery in the U.S. is related to consistency. He explains:

“Electricity in the United States is generated, transported and delivered by alternating current (AC). But modern devices—from renewable power resources and electric vehicles to high-definition televisions, data center, computers and other devices take a direct current (DC) input, hence the AC/DC converters.” In short, systems that were once adequate are now strained due to a lack of IT infrastructure to support added complexity.

Others are looking at the roles that smart meters can play within paradoxical issue of cloud computing data centers themselves. In other words, they are examining how data centers that provide the cloud power to create better efficiency can themselves become more central to overall local efficiency.

The cloud can provide a robust, scalable system to manage fluctuating demand and input/output of information as well as serve as a springboard for creative teams of developers. However, it’s a long road ahead. In the meantime, the urban migration continues to build, making the work to support energy efficiency via cloud computing (and other IT innovations) an urgent matter.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

TACC Helps ROSIE Bioscience Gateway Expand its Impact

April 26, 2017

Biomolecule structure prediction has long been challenging not least because the relevant software and workflows often require high-end HPC systems that many bioscience researchers lack easy access to. Read more…

By John Russell

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

IBM, Nvidia, Stone Ridge Claim Gas & Oil Simulation Record

April 25, 2017

IBM, Nvidia, and Stone Ridge Technology today reported setting the performance record for a “billion cell” oil and gas reservoir simulation. Read more…

By John Russell

ASC17 Makes Splash at Wuxi Supercomputing Center

April 24, 2017

A record-breaking twenty student teams plus scores of company representatives, media professionals, staff and student volunteers transformed a formerly empty hall inside the Wuxi Supercomputing Center into a bustling hub of HPC activity, kicking off day one of 2017 Asia Student Supercomputer Challenge (ASC17). Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Remote Visualization Optimizing Life Sciences Operations and Care Delivery

As patients continually demand a better quality of care and increasingly complex workloads challenge healthcare organizations to innovate, investing in the right technologies is key to ensuring growth and success. Read more…

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of a new generation of chips designed specifically for deep learning workloads. Read more…

By Alex Woodie

Musk’s Latest Startup Eyes Brain-Computer Links

April 21, 2017

Elon Musk, the auto and space entrepreneur and severe critic of artificial intelligence, is forming a new venture that reportedly will seek to develop an interface between the human brain and computers. Read more…

By George Leopold

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

NERSC Cori Shows the World How Many-Cores for the Masses Works

April 21, 2017

As its mission, the high performance computing center for the U.S. Department of Energy Office of Science, NERSC (the National Energy Research Supercomputer Center), supports a broad spectrum of forefront scientific research across diverse areas that includes climate, material science, chemistry, fusion energy, high-energy physics and many others. Read more…

By Rob Farber

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

ASC17 Makes Splash at Wuxi Supercomputing Center

April 24, 2017

A record-breaking twenty student teams plus scores of company representatives, media professionals, staff and student volunteers transformed a formerly empty hall inside the Wuxi Supercomputing Center into a bustling hub of HPC activity, kicking off day one of 2017 Asia Student Supercomputer Challenge (ASC17). Read more…

By Tiffany Trader

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of a new generation of chips designed specifically for deep learning workloads. Read more…

By Alex Woodie

NERSC Cori Shows the World How Many-Cores for the Masses Works

April 21, 2017

As its mission, the high performance computing center for the U.S. Department of Energy Office of Science, NERSC (the National Energy Research Supercomputer Center), supports a broad spectrum of forefront scientific research across diverse areas that includes climate, material science, chemistry, fusion energy, high-energy physics and many others. Read more…

By Rob Farber

Hyperion (IDC) Paints a Bullish Picture of HPC Future

April 20, 2017

Hyperion Research – formerly IDC’s HPC group – yesterday painted a fascinating and complicated portrait of the HPC community’s health and prospects at the HPC User Forum held in Albuquerque, NM. HPC sales are up and growing ($22 billion, all HPC segments, 2016). Read more…

By John Russell

Knights Landing Processor with Omni-Path Makes Cloud Debut

April 18, 2017

HPC cloud specialist Rescale is partnering with Intel and HPC resource provider R Systems to offer first-ever cloud access to Xeon Phi "Knights Landing" processors. The infrastructure is based on the 68-core Intel Knights Landing processor with integrated Omni-Path fabric (the 7250F Xeon Phi). Read more…

By Tiffany Trader

CERN openlab Explores New CPU/FPGA Processing Solutions

April 14, 2017

Through a CERN openlab project known as the ‘High-Throughput Computing Collaboration,’ researchers are investigating the use of various Intel technologies in data filtering and data acquisition systems. Read more…

By Linda Barney

DOE Supercomputer Achieves Record 45-Qubit Quantum Simulation

April 13, 2017

In order to simulate larger and larger quantum systems and usher in an age of “quantum supremacy,” researchers are stretching the limits of today’s most advanced supercomputers. Read more…

By Tiffany Trader

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference phase of neural networks (NN). Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Leading Solution Providers

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. Read more…

By Tiffany Trader

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This