One of the most obvious trends from the big smart grid conference DistribuTECH last week was how much analytics and big data tools will be used to try to remake energy in 2012, from curbing energy consumption, to reducing energy loss, to adding in more clean power to the grid. Here’s 10 ways that analytics and big data will start to shape the production and consumption of energy in the world:

1). Weather data: Having a finger on the pulse of constantly changing weather data on a micro and macro level can help utilities, building owners and consumers optimize their energy consumption habits and promote energy efficiency. Startup EnergyHub recently partnered with sensor network player Earth Networks to use weather data to make a more efficient form of demand response (utilities controlling power consumption). Other startups like EcoFactor, Opower and Tendril also use weather data as part of their energy behavioral analytics.

IBM has long sold a weather prediction service called Deep Thunder to municipalities, organizations and utilities, which use it to do things like tailor their services, change routes, or generate more or less power. I think weather data could some day provide a platform for some very important next generation services and applications for energy efficiency, much in the way that location data is used as a platform for a variety of services.

2). Cell phone data: Cell phones in our pockets are essentially palm-sized sensors and computers sending a constant stream of information to the cloud where companies could one day use that data to create energy efficiency and better energy products. And yes, a lot of that data is private information, but after that data is anonymized it can be used for the greater good of the community — particularly via the billions of cell phones in developing countries. A startup called Jana does research projects around cell phone data in developing countries, and looks to work with NGOs on programs to create better infrastructure, energy infrastructure and resources.

3). Connected thermostat data: One of the biggest trends from DistribuTECH this year was the overwhelming amount of smart thermostats that are now being sold and marketed. Companies can incorporate that thermostat data into data bases that can be used to promote energy efficiency. EcoFactor’s service remembers every time a home owner overrides the automated smart thermostat system and changes the personalized service to accommodate that manual override. Using 100,000 connected thermostats (which produce 5 billion data points each month) EnergyHub found some interesting statistics like folks in cold climates have a lower average heating temperature set point than households in warmer states.

4). Hadoop & energy databases: The open source data base tool Hadoop is well known — and oft used — in the computing worlds. But in the energy and utility worlds it’s quite rare. However, as the amount of energy data has started to rapidly grow from the smart grid, some companies are embracing Hadoop as a key way to manage energy info. Opower tells me it’s using Hadoop (and the company commercializing Hadoop, Cloudera) as an important way to manage its massive energy data streams. Likewise PJM has turned to Hadoop as a way to organize the energy data coming off of a synchophaser sensor project.

5). Clean power data: One of the main goals for the smart grid is to enable the addition of more variable clean power, which is far more unreliable than fossil fuels (the sun doesn’t shine and the wind doesn’t blow 24/7). Analytics crunching the data from a utilities’ energy supply and demand can help make clean power a little less variable, by being able to more accurately predict the environmental conditions, as well as more accurately assess demand from energy users.

6). Electric car data: Electric cars will by their nature be connected cars, using information technology to manage the vehicle charge and location. Utilities will be closely tracking the charging habits of electric car owners in order to make sure that the grid isn’t overloaded in some early adopter neighborhoods.

7). Power line sensors: One of the areas of low hanging fruit for the power grid is the simple task of helping utilities find blackouts more easily and be able to monitor and manage grid outages. That’s partly where sensor systems called synchophasers come in, which can in real time monitor the health of power lines, collecting multiple data streams per second. Expect all major networks to have synchophaser systems installed over the coming years.

8). Real estate data: Startups like First Fuel Software can use big data to make super accurate assessments about buildings and ways to reduce the energy consumption of buildings — without any extra hardware or monitoring software being installed at the building. Things like weather around the building, demographics of the people in the building, and the building’s historical energy consumption can be used to create an accurate projection. The best way to make a building more energy efficient is by getting as much data about the building;s energy use as possible.

9). Variable pricing: Some day when electricity is sold throughout the world at different prices dependent on supply and demand, massive data bases will be needed. This type of variable pricing is offered in some places in the world, but if it ever becomes ubiquitous it will help curb consumption, by offering high prices when energy is being over used.

10). Using behavioral analytics to curb energy consumption: Getting into the brains of energy users is the job of startups like Opower and Tendril (after it acquired Gr0unded Power.) Essentially these companies have collected data on consumers and demographics and they are using it to try to guess the best way to influence the consumer to do things like upgrade their home appliances and lights to more efficient ones.

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Mobility has changed the chip industry already, but the rise of the iPhone and devices such as e-readers are only the beginning. If we’re going to create an Internet of things that connects back to a cloud powered by millions of servers, the chip world will have to change drastically to reduce power consumption, shrink in size and embrace new architectures. Fortunately these things are already happening, and here are three startups that showcase the big upcoming shifts.

SuVolta

SuVolta doesn’t want to design chips, it wants to make the process that fabrication plants will use to build the devices. Its technology cuts the energy used in chips in half, and requires a fairly simple tweak of the chemicals layered onto the chip during the manufacturing process. The resulting chips made using SuVolta’s process are just as fast but consume about half the power.

This power reduction is cool, but it’s not the main reason why SuVolta’s on this list. SuVolta tweaks both the manufacturing process and the circuit design. But the process works best for systems on a chip, as opposed to stand alone processors. A System on a chip (SoC) is when multiple types of processors are placed on a single chip as an integrated package.

SoCs are common in the mobile world because they are a way to cram more functionality into a smaller package and they consume less power. SuVolta’s President and CEO Bruce McWilliams, believes SoCs will be the way of the future for how most chips are built.

Ambiq Micro

Ambiq is commercializing technology out of the University of Michigan to build a real-time clock designed for sensors. The clock consumes less power, but also takes over functions that currently involve other chips in order to reduce the power usage of the sensor even further (yup, it’s like an SoC microcontroller). Scott Hanson, the CEO and co-founder of Ambiq explains that today’s sensors usually contain a microcontroller, a clock that puts the chip to sleep and wakes it as necessary, a power supply, a sensor of some sort (typically a MEMs device) and a radio.

But Ambiq combines the clock and the microcontroller so the chip requires less power and takes up less space. Some proposed uses of the chip include implanting it inside the human body, or a chip that can run on tiny solar cells the size of a penny (see image).

As we put more sensors on devices and inside our infrastructure, Hansen believes we’re about to open up a new frontier for chip design firms who can build chips for the sensor web. Ambiq is his bet on this, but he expects many more. With an investment from ARM, he’s not the only one betting on a new generation of chips that will need specialized microcontroller and a smaller size, the British licensing company clearly sees an opportunity as well.

Adapteva

The demand for power in mobile devices and in the servers that power large web sites such as Facebook or Google has led to a boost for ARM, which licenses a chip architecture that trades performance speed for power efficiency. For phones this is fine, but for tablets and even servers, it may be time to think up an entirely new architecture. That’s where Adapteva comes in. The company has rethought a RISC-based architecture for chips and built massively multicore chips that are built to run in parallel or independently.

Much like an older startup called Tilera, which is also building massively multicore chips for data centers, Adapteva thinks that x86 doesn’t offer the energy efficiency needed, while ARM doesn’t offer the performance that next generation mobile devices such as tablets and servers will need. So it’s borrowing the concept of massively multicore chips from the high performance computing world and dialing it down for tomorrow’s mobile applications and up for the next generation of HPC. In the coming years, we’ll see more massively parallel chips, but we’ll also see a willingness to jettison the tried and true architectures as we embrace more specialty computing.

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As the internet expands — and businesses bring more and more data online — it’s more important the ever that data centers keep their power consumption down. This not only saves money, it eases the burden on the environment. Raising temperatures is one rather easy way to save power, but many data operators are afraid to dial up the savings. They’re afraid of damaging equipment. They’re afraid of voiding warranties. They’re afraid of change. Theses fears appear to be unwarranted, but there’s been little in the way of hard data to dispel them. That’s beginning to change, however, as the large data center operators such as Amazon and Facebook study the problem internally and equipment makers such Intel conduct experiments and educate customers

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A fresh contender for your blow-out 2012 Olympic gaming rig: AMD’s first 28nm GPU, the Radeon HD 7970. It’s scheduled to arrive on January 9th, priced at 9 — nearly 0 more than its direct ancestor, the 6970. Then again, this newcomer packs some supremely athletic specs, including a 925MHz engine clock that can be readily OC’d to 1.1GHz, 2,048 stream processors and an uncommonly muscular 384-bit memory bus serving 3GB of GDDR5. At the same time, AMD hopes to make the card more practical than the dual-processor 6990 by bringing the card’s power consumption down to less than 300W under load and a mere 3W in ‘long idle’ mode, and promising quieter cooling thanks to improved airflow and a bigger fan. We’ll have to wait for benchmarks in January before we hand out any medals, but in the meantime NVIDIA’s forthcoming 28nm Kepler GPU might want to step up its training schedule.

Continue reading AMD announces next-gen Radeon HD 7970 for 9, says it ‘soundly beats’ rivals

AMD announces next-gen Radeon HD 7970 for 9, says it ‘soundly beats’ rivals originally appeared on Engadget on Thu, 22 Dec 2011 00:01:00 EDT. Please see our terms for use of feeds.

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Sure, Sprint swill deploy LTE-Advanced in 2013, which has the capability to offer gigabit speeds on fixed networks, but Samsung is actually talking about ways we can get multi-gigabit networks on wireless. Speaking at the Texas Wireless summit, Jerry Pi, a researcher with Samsung, showed how we can use millimeter wave spectrum to deliver up to 5.5 gigabit per second wireless connections.

While, Pi declined to say how far off something like this is, Ted Rappaport, director of the Wireless Networking and Communications Group with the University of Texas and the host of the conference said he imagined this sort of technology being about 5 years out. Indeed, Pi showed ways that a test network using millimeter wave broadband could be built today. Of course, to build a fully functioning mobile broadband network, many elements have to come together–some of which are out of Samsung’s control.

For example, the airwaves have to be available in the millimeter wave band, which sits between 3 GHz and 300 GHz. Pi estimates there are 250 gigahertz of spectrum available in these bands, and some of them are already licensed for broadband services. For example, the FCC has regulated spectrum in the LMDS band for fixed wireless broadband, but a change to allow mobile wireless broadband might be easy to implement.

Once the spectrum is in place, radios can follow. There have been plenty of advancements in radio technology in some of the millimeter wave bands, that means radios can be produced cheaply using conventional semiconductor manufacturing methods and materials. But there are engineering challenges associated with building a wireless network in the higher frequencies–problems posed by water, trees and oxygen.

Because of the peculiarities of physics and working at higher frequencies building a network using higher frequencies will require news ways of engineering networks. They may alos require greater power consumption, both on the device and at the base station. At higher frequencies the spectrum tends to falter when it hits water, sometimes oxygen molecules and trees, not to mention buildings and walls. Pi says Samsung is looking at using beam-forming to deliver bits over that spectrum, and large portions of his presentation dealt with how those might be built and arrayed. Here’s an earlier version of his presentation for the truly nerdy.

However, the rewards of overcoming these challenges in a cost effective way are apparent. As the chart above illustrates, the opportunity here is to deliver multiple gigabits per second on wireless networks (see chart). Mobile broadband demand won’t abate anytime soon, so figuring out ways to deliver faster speeds on relatively unoccupied spectrum is already an imperative for the industry. Pi mentioned the gap that carriers face when it comes to delivering data, and how a lack of profitability could threaten the industry.

Pi however, took a far more practical and innovation-friendly view on the looming revenue gap for carriers, saying, “Don’t expect you can make a thousand times more money just by carrying a thousand times more traffic.” Indeed, the cellular industry doesn’t follow the same cost curve that Moore’s Law has allowed for computing, but given user demand, it may have to get closer. Millimeter broadband may help.

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