Mike Prawicki

Mike Prawicki – Things I find interesting, amusing and well…..

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Cisco buys into WiMax for Smart Grid, acquires stake in Grid Net

Mar 26

Posted by Mike Prawicki in News, Tech | No Comments

Cisco Systems has been scouting for major plays in the Smart Grid infrastructure arena for about a year — some analysts even speculated that it would buy wireless networking provider Silver Spring Networks. But today, it announced its decision to go with Grid Net, one of the first and only companies to trumpet WiMAX as the ultimate solution for transmitting data between utilities and smart meters.

Most utilities and meter makers rely on cellular networks or proprietary broadband networks to get the job done, arguing that WiMAX is still too expensive for broad deployment. But Grid Net says price won’t be an issue for long. Not only does WiMAX offer higher speeds and more bandwidth, but it will be extremely cheap in the future because it’s an open standard, says Grid Net CEO Ray Bell.

So far, it’s unclear exactly what Cisco wants with the company’s WiMAX expertise. It’s made a lot of noise about being a major force in the Smart Grid market, appointing Laura Ipsen to head up a dedicated program, and announcing that it would dedicate unlimited budget to the cause.

But so far, the company has little to show for it. At VentureBeat’s GreenBeat conference in November, Ipsen said Cisco would be rolling out its first Smart Grid networking products in the first half of 2010, but this remains to be seen.

The deal makes sense, considering that Bell formerly worked on networking solutions at Cisco. One can assume that he giant will be integrating WiMAX into its own Smart Grid products when they do hit the market. Even being involved in WiMAX development puts Cisco on the cutting edge of the Smart Grid industry.

I reported yesterday on the scuffle between companies promoting public network communications (SmartSynch) and those endorsing private networks (Trilliant, Silver Spring). If WiMAX comes along as fast as Grid Net says it will, it could immediately trump both of those options.

Some Smart Grid players have dismissed WiMAX out of hand, but it looks like that’s the direction the whole industry might move. In addition to Cisco buying into WiMAX, General Electric also announced today that it’s launching its own Smart Grid pilot project that will test WiMAX in tandem with Consumers Energy, a utility based in Michigan.

This is also the second big recent win for Grid Net, which just snagged Austin Energy Chief Information Officer Andres Carvallo to sell the idea of WiMAX to utilities. Carvallo is credited with spearheading the country’s first Smart Grid deployment in Texas.

From GreenBeat March 25, 2010 | Camille Ricketts

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Remembering the future: Our brain saves energy by predicting what it will see

Mar 25

Posted by Mike Prawicki in Health | No Comments

(PhysOrg.com) — Researchers have discovered that the brain saves energy by predicting what it is likely to see. According to scientists in the Department of Psychology at the University of Glasgow in collaboration with the Max-Planck Institute for Brain Research, Frankfurt, Germany, the visual cortex does not simply react to visual stimuli but proactively predicts what it is likely to see in any given context – for example, within familiar environments such as your house or office.

By doing so it uses less energy to process images, but if something unexpected were to appear in that familiar environment, the visual cortex becomes more active in order to process this information.

“Imagine your desk in your office,” said lead researcher Dr Lars Muckli. ”You’ve seen it a million times so your brain knows what it looks like so it doesn’t need to spend lots of time processing the scene. It already has a mental image of it and so the brain predicts that this is what it will see before you walk into the room.

“However, if you were to walk in to your office one day and see someone totally unexpected sitting in your chair – the Prime Minister, for example, your brain would have to work harder to process the same scene.”

The findings build on a fairly new hypothesis developed by University College London neuroscientist Karl Friston called predictive coding – or free energy principle – which suggests the brain is actively predicting what input it will receive, rather than just passively processing information as it arrives.

Dr Muckli said: “By predictive coding we refer to the idea that the brain generates predictions that estimate the visual input it will most likely receive given the contextual information from the recent past. For the brain it’s really about surprise reduction.”

To test the predictive coding hypothesis, the Glasgow researchers conducted an experiment where 12 volunteer subjects were asked to view a visual stimulus while undergoing and fMRI brain scan.

The subjects had to look at a fixed point on a computer screen above and below which two dots would flash alternatively creating an illusion of motion.

For predictable/unpredictable trials, the researchers briefly presented a third dot on the screen. To test predictable stimulus the dot would appear at a point between the two other dots, timed to correlate to the illusion of smooth movement. For the unpredictable stimulus it would appear out of sync with the motion illusion.

The primary visual cortex (V1) of each subject was monitored while the tests were undertaken and the results showed that the predictable patterns resulted in less activity in V1, compared to the unpredictable stimulus.

Dr Muckli said: “The brain expects to see things and really just wants confirm it now and again – it’s almost like remembering the future.

“It might explain why sometimes you don’t notice something different in a familiar environment because your brain is seeing what it expects to see, rather than what is actually there.

“What we need to do now is extend this research to consider predictive coding in more natural environments and other aspects of sensory perception.”

The paper, ‘Stimulus Predictability Reduces Responses in Primary Visual Cortex’, was published in the Journal of Neuroscience.

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Wind Farms And Global Warming

Mar 12

Posted by Mike Prawicki in News, Tech | No Comments

Wind resistance

MIT analysis suggests generating electricity from large-scale wind farms could influence climate — and not necessarily in the desired way.

Morgan Bettex, MIT News Office

Wind power has emerged as a viable renewable energy source in recent years — one that proponents say could lessen the threat of global warming. Although the American Wind Energy Association estimates that only about 2 percent of U.S. electricity is currently generated from wind turbines, the U.S. Department of Energy has said that wind power could account for a fifth of the nation’s electricity supply by 2030.

But a new MIT analysis may serve to temper enthusiasm about wind power, at least at very large scales. Ron Prinn, TEPCO Professor of Atmospheric Science, and principal research scientist Chien Wang of the Department of Earth, Atmospheric and Planetary Sciences, used a climate model to analyze the effects of millions of wind turbines that would need to be installed across vast stretches of land and ocean to generate wind power on a global scale. Such a massive deployment could indeed impact the climate, they found, though not necessarily with the desired outcome.

In a paper published online Feb. 22 in Atmospheric Chemistry and Physics, Wang and Prinn suggest that using wind turbines to meet 10 percent of global energy demand in 2100 could cause temperatures to rise by one degree Celsius in the regions on land where the wind farms are installed, including a smaller increase in areas beyond those regions. Their analysis indicates the opposite result for wind turbines installed in water: a drop in temperatures by one degree Celsius over those regions. The researchers also suggest that the intermittency of wind power could require significant and costly backup options, such as natural gas-fired power plants.

Prinn cautioned against interpreting the study as an argument against wind power, urging that it be used to guide future research that explores the downsides of large-scale wind power before significant resources are invested to build vast wind farms. “We’re not pessimistic about wind,” he said. “We haven’t absolutely proven this effect, and we’d rather see that people do further research.”

Daniel Kirk-Davidoff, a chief scientist for MDA Federal Inc., which develops remote sensing technologies, and adjunct professor of meteorology at the University of Maryland, has examined the climate impacts of large-scale wind farms in previous studies. To him, the most promising result of the MIT analysis is that it indicates that the large-scale installation of wind turbines doesn’t appear to slow wind flow so much that it would be impossible to generate a desirable amount of energy. “When you put the wind turbines in, they are generating the kind of power you’d hope for,” he said.

Tapping the wind resource

Previous studies have predicted that annual world energy demand will increase from 14 terawatts (trillion watts) in 2002 to 44 terawatts by 2100. In their analysis, Prinn and Wang focus on the impact of using wind turbines to generate five terawatts of electric power.

Using a climate model developed by the U.S. National Center for Atmospheric Research, the researchers simulated the aerodynamic effects of large-scale wind farms — located both on land and on the ocean — to analyze how the atmosphere, ocean and land would respond over a 60-year span.

For the land analysis, they simulated the effects of wind farms by using data about how objects similar to turbines, such as undulating hills and clumps of trees, affect surface “roughness,” or friction that can disturb wind flow. After adding this data to the model, the researchers observed that the surface air temperature over the wind farm regions increased by about one degree Celsius, which averages out to an increase of .15 degrees Celsius over the entire global surface.

According to Prinn and Wang, this temperature increase occurs because the wind turbines affect two processes that play critical roles in determining surface temperature and atmospheric circulation: vertical turbulent motion and horizontal heat transport. Turbulent motion refers to the process by which heat and moisture are transferred from the land or ocean surface to the lower atmosphere. Horizontal heat transport is the process by which steady large-scale winds transport excessive heat away from warm regions, generally in a horizontal direction, and redistribute it to cooler regions. This process is critical for large-scale heat redistribution, whereas the effects of turbulent motion are generally more localized.

In the analysis, the wind turbines on land reduced wind speed, particularly on the downwind side of the wind farms, which reduced the strength of the turbulent motion and horizontal heat transport processes that move heat away from the Earth’s surface. This resulted in less heat being transported to the upper parts of the atmosphere, as well as to other regions farther away from the wind farms. The effect is similar to being at the beach on a windy summer day: If the wind weakened or disappeared, it would get warmer.

In contrast, when examining ocean-based wind farms, Prinn and Wang found that wind turbines cooled the surface by more than one degree Celsius. They said that these results are unreliable, however, because in their analysis, they modeled the effects of wind turbines by introducing surface friction in the form of large artificial waves. But they acknowledge that this is not an accurate comparison, meaning that a better way of simulating marine-based wind turbines must be developed before reliable conclusions can be made.

In addition to changes in temperatures and surface heat fluxes, they also observed changes in large-scale precipitation, particularly at the mid-latitudes in the Northern Hemisphere. Although these changes exceeded 10 percent in some areas, the global total changes were not very large, according to Prinn and Wang.

To investigate the effect of wind variability on the intermittency in wind power generation, the researchers used the climate model to estimate the monthly-mean wind power consumption and electrical generation for each continent, concluding that there are very large and geographically extensive seasonal variations, particularly over North and South America, Africa and the Middle East. They explain that this unreliability means that an electrical generation system with greatly increased use of wind turbines would still require backup generation even if continental-scale power lines enabled electrical transmission from windy to non-windy areas.

Although Prinn and Wang believe their results for the land-based wind farms are robust, Wang called their analysis a “proof-of-concept” study that requires additional theoretical and modeling work, as well as field experiments for complete verification.

Their next step is to address how to simulate ocean-based wind farms more accurately. They plan to collaborate with aeronautical engineers to develop parameters for the climate model that will allow them to simulate turbines in coastal waters.?

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