Turn your office expense reports into toilet paper
Ever feel like the paper you handle at work every day isn’t worth wiping your butt with? Well, a Japanese machine can turn it all into toilet paper. Magically.

Originally posted at Crave

Visit the original post at: Green Tech

Demolishing and Building a House with No Dumpster: The REX Project (Video)

Image credit: Shannon Quimby

Although we know that reuse should come before recycle, it’s a sad truth that the reuse industry is often overlooked when people talk about green building. But one woman is out to change all that—literally recycling/reusing an entire dilapidated house as she builds her new home. That’s right, she’s demolishing an old home, and building a new house, without using a dumpster…. Read the full story on TreeHugger
Visit the original post at: TreeHugger

Top Fashion Designers Think Fair Trade for EJF Cotton Campaign

The Environmental Justice Foundation (EJF) has just launched a set of sustainable t-shirts designed by the likes of haute couturiers John Rocha, Zandra Rhodes, Luella Bartley, and Christian Lacroix — to name a few — for summer 2010. The t-shirts are made with fairly traded Continental cotton from Turkey are are designed around the theme, “childhood, lost innocence and hope” in light of EJF’s newly release report, “Slave Nation” on their campaign to end child labor in Uzbekistan. It’s looking las… Read the full story on TreeHugger
Visit the original post at: TreeHugger

Top Fashion Designers Think Fair Trade for EJF Cotton Campaign

The Environmental Justice Foundation (EJF) has just launched a set of sustainable t-shirts designed by the likes of haute couturiers John Rocha, Zandra Rhodes, Luella Bartley, and Christian Lacroix — to name a few — for summer 2010. The t-shirts are made with fairly traded Continental cotton from Turkey are are designed around the theme, “childhood, lost innocence and hope” in light of EJF’s newly release report, “Slave Nation” on their campaign to end child labor in Uzbekistan. It’s looking las… Read the full story on TreeHugger
Visit the original post at: TreeHugger

In clean energy, U.S. needs more steel in ground
Researching technology breakthroughs is worthwhile, but people in renewable energy say the U.S. needs to speed up installation of products to lower costs and stay competitive globally.
Visit the original post at: Green Tech

Ocean Film Fest 2010: It’s Not If, But How Military Sonar Kills Whales (Video)

Photo via Wolfiewolf

Are human-generated noises killing the oceans? This is the question posed by Michael Stocker of the Ocean Conservation Research organization and Volker Barth, creator of Sounds of the Sea, a documentary exploring how military sonar operations are the cause of whale and porpoise strandings and deaths. Not if, but how. In this extraordinary film, researchers reveal the way in which sonar impacts whales’ bodies, how it causes internal bleeding, deaths, and strandings, and why … Read the full story on TreeHugger
Visit the original post at: TreeHugger

Low speed wind power generator could take weight out of the nacelle

The weight of wind turbine generators is a significant issue because weight translates to costs. The structural weight of a direct-drive generator, for example, can exceed 80% of the total weight on the tower. The structure is needed to overcome the force of magnetic attraction between stationary and moving parts. The attraction force, a result of the normal component of Maxwell stress, can be 10 times the torque producing shear stress. The function of the generator structure is to maintain an airgap between the rotor and stator.

Ideally, a directly-driven generator should produce moderate to high shear stress while negating the effect of the magnetic attraction. A new topology has potential to meet that challenge, without resorting to exotic structural or magnetic materials such as superconductors. The concept takes the active materials in the machine – copper, magnets and steel – and changes their relative positions to minimize the normal-force effects. The result is a structure that need only support the weight of the active components, leading to a reduction of about 55% compared to conventional permanent magnet (PM) machines. Results show the weight reduction while maintaining high efficiency at all loads. Experimental results from a 20kW, 100 rpm prototype verify the expected performance.

Design details

The new design is air-cored, meaning there is no iron in the stator so there is little attraction between rotor and stator. In two-sided axial-flux air-cored machines, the two rotors attract each other. Because the airgap-flux density, B, is lower than for an iron-cored machine, the shear stress, ?, is lower as shown by

? ? BJ (1)

where J = current density, A/mm2. The current density in the generator coils is limited by copper losses and cooling requirements. To produce the same torque, T, the outer radius, ro, of an axial-flux machine must increase to accommodate the lower shear stress because

where kr = ratio of inner to outer radii.

The increase in machine radius, when moving from iron-cored to air-cored designs can cancel the expected reductions in structural weight. One wind turbine design from Goliath Wind OU, Estonia, proposes an ironless radial-flux generator which has no airgap closing force. This is accomplished with an ironless outer stator. Its generator has a large radius, R, held in place by a lightweight spoked structure. The ironless stator produces a large airgap, so its flux density and shear stresses are small. A large air-gap radius is needed because of the low shear stress. Equation 3 is the radial-flux equivalent of Equation 2,

where L = axial length. A previous simple study showed that air-cored machines are potentially lighter for a range of power ratings.

Developing a C-core machine

A logical development of such axial-flux disc machines is to increase the rotor-shaft radius. Because airgap normal forces act near the junction of shaft and discs, the discs can be made thinner and therefore lighter. Taking this further leaves a C-shaped cross section, where the limbs carry magnets and the stator winding is held independently between them. A further step lets flux cross the web of the C and makes the rotor out of modules each carrying a pair of magnets. Rotating the C-core modules 90° produces a radial flux machine. Increasing the axial length allow increasing the radial-flux generator’s torque rating without increasing the outer diameter.

This topology has advantages over existing ironless designs. A radial-flux ironless permanent magnet machine has a large effective airgap. This C core machine, however, has a smaller airgap length making possible higher flux densities and shear stresses. A corollary is that less permanent-magnet material is needed to produce the same flux density, so the design will be cheaper. This machine also has the advantage of two main flux paths, longitudinal and transversal, not just one. Because the amount of magnetically active steel depends on its non-saturation, this should be a lighter design than an axial-flux, two-disc machine.

Active and inactive material

The new topology is structurally superior to an iron-cored machine. In a conventional radial-flux machine, large airgap normal forces can act at distances of several meters from points where these forces can be reacted against. This implies that the rotor and stator structures must be stiff, large, and heavy. In contrast the new machine has no forces on the stator. Although the two limbs of the C-core are attracted to each other, normal stresses are reacted at points within the C-core – close to their point of application. This topology means that the steel in the C-core fulfills both active and inactive roles.

To test the ideas, a 20kW, 100rpm generator was designed at the University of Edinburgh and built by Fountain Design Ltd. (fountaindesign.co.uk) It is instructive to describe the build sequence and highlight topology’s manufacturing advantages. The rotor of the prototype C-core machine was made of 32 modules, each carrying a pair of permanent magnets similarly oriented. In this small machine, the C-core module was assembled from three trapezoidal pieces of mild steel, with magnets sliding onto the inner and outer pieces. For larger machines, magnetic material could be glued in place and magnetized later.

This would ease the problems of handling large magnets. Modularity allows the cheap and efficient production of large volumes. An assembled module is quite benign and safe to handle, because there is relatively little leakage flux outside the confines of the C core. The modules can be brought together and fixed to a common rotor structure. The prototype uses an aluminum disc.

Bringing together a rotor and stator can be a difficult and dangerous task in a conventional permanent-magnet machine because of the large magnetic attractions. Doing so is liable to pull either the rotor or stator off center and produce an unbalanced magnetic pull, thereby closing the airgap clearance even further.

A feature of the C core machine is that because there is no iron in the stator, there is no force of attraction between rotor and stator. This makes a straightforward task of threading the stator winding into the rotor. The stator in the prototype is made of 24 pseudo arc shaped concentrated coils, clamped between two rings. The coil’s discrete nature means they will be easy to replace. This will be a significant advantage in larger machines, as electrical faults are one of the more common causes of failure in direct-drive wind-turbine generators.

The prototype

The 20kW prototype machine generated a perfectly sinusoidal no-load voltage waveform of 26.7 Hz frequency at 100 rpm. A power-versus-efficiency chart gives the mechanical-to-electrical efficiency of the prototype generator over a range of speeds for a range of loads, typical for this size machine. Results show that the design matches the performance of conventional PM synchronous generators.

Thinking bigger

Conventional PM machines tend to have optimal aspect ratios (axial length to airgap diameter). In terms of electromagnetically active material, less of it is needed with a small aspect ratio and large airgap radius, R. This is because the active weight is almost proportional to the airgap surface area (2?RL) whereas the torque, according to Equation (3), is proportional to R2L. Increasing the radius therefore increases the specific torque (with respect to the active weight).

There are two limits to how small the aspect ratio can be. There is a practical limit to how big the airgap diameter can be so that the generator can be transported and fit into a nacelle. The second limit is the structural material: the structural weight of a radial-flux machine is proportional to the square of the airgap radius (for a constant axial length and for a deflection fixed in relation to the airgap clearance). The C-core machine follows the same scaling laws for active weight, but has a different law for the structural material.

In C-core modules, limbs deflect into the airgap by:

where y = deflection, w = uniformly distributed load and a product of the normal component of Maxwell stress and the width of the limb. l = length of the cantilevered beam, and A = the second moment of area.

For a fixed axial length and a trapezoidal cross section, the weight of structural material, wstr (needed to limit y to a fixed proportion of the airgap clearance) is related to the airgap radius by:

This means the specific torque with respect to structural weight also rises with increased airgap radius.

The Generator weight and airgap charts show the generator weight based on the C core concept for 100 kW to 2 MW wind turbines. The electromagnetic design used the same basic pole pitch layout as the 20kW machine, with the number of poles and coils varied proportionately to the airgap radius.
The airgap clearance above and below the coil was taken as 0.1% of the airgap diameter. The magnetic flux was modeled using a simple lumped parameter magnetic circuit and the iron was not allowed to saturate.

For structural modeling, the maximum deflection of a C-core limb was restricted to 10% of the airgap clearance. Generator mass versus power show results for five different axial active lengths. As expected, designs with an active length of 0.4m are lightest because they reduce the active and structural weight. At larger ratings, these axially short machines may not be practical because of their large airgap diameters. Even the axially longest have great promise because these designs are not yet optimized for minimum weight.

Visit the original post at: Wind Power News

Here’s what I think, Feb 2010:Paul Dvorak

Economic conditions don’t look good right now. Our nation is at war, businesses struggle to get sales going, and the future feels uncertain. To make matters worse, baby boomers, the most experienced people in your company, are thinking about retirement and some will take advantage of it. If there ever was a time that called for solid new leadership, this is it.

The question is, how do you find leaders for your company? The answer is you don’t. You train them. A good reason for doing so comes from Jim Collins’ book “From good to great”. In it, he reports on researchers who evaluated a range of similar companies led by CEOs hired outside the firm and those run by people who rose through the ranks. The good news is that the home grown CEOs generally outperformed the hired guns.

Although I’m no leadership expert, working with people over the last half century has led me to recognize several traits useful in a leader. Sooner or later you’ll be asked to head a project or department. So consider cultivating these characteristics:

For goodness sakes, show some enthusiasm. Let your people know you’re glad to be there. No one enjoys working for a stoic. When a staffer does something right, let them hear your appreciation. Remember: Praise in public, criticize in private.

Listen to your team. They are chock full of good ideas. You just have to ask for them. Ask them in small groups because people seem more willing to share in the comfort of, say, two to five peers.

Don’t underestimate quiet people. One former colleague was the quietest on staff, especially when in an audience. At press conferences she rarely asked questions or made comments. But when asked for a suggestion away from the crowd, she always offered a worthy idea.

Back up your followers because sometimes the cantankerous client is not always right. This is where your diplomatic and negotiating skills come in.

Let your team know what is going on and what you expect of them. Set clear group goals. You’ll expect them to talk to you so talk to them as well. Tell them how the department is doing and ask for ideas how it might do better. Be honest. They will know when you’re not and that can hurt your credibility.

Cultivate the peculiar genius. Most groups have one. Sometimes they are unsociable, easily riled, and may easily irritate others because of their unconventional manner. You need their special skills and out-of-the-box thinking, so let them be peculiar. And lastly:

Be nice to the gray-hairs. Maybe a few will stick around and you’ll learn something new.

Wind energy and leadership

The renewable industry is a growing endeavor with windpower in a leadership role showing what can be done with the right ideas and goals. Every company in the wind industry has an opportunity to be a leader by delivering on the promises and expectations that wind can be the world’s most efficient renewable energy. Join the sponsoring companies in this issue and me as we deliver on those expectations and promises.

Visit the original post at: Wind Power News

A blast from the past: Flower power returns

The flower, by Art Energy Design, is a renewable energy display with solar cells attached to leaves while the flower petals act as a rotor to turn a 6V generator. Both charge a battery in the base that stores enough energy to keep the display lit by LEDs at night.

The Pittsburgh Power Flowers Project says it combines sustainable energy devices with a variety of artistic designs. “Power Flower public art sculptures are one example of our mission-specific design series,” says Dave Edwards, artist and spokesman for the organization. The flower is intended to demonstrate thought-provoking ways wind, solar, and recycling ideas can be built into urban landscapes.

“Understand that we are artists, not engineers,” adds Edwards. “The real power of our Power Flower is the conversation it starts about sustainable energy. We have created an educational tool that uses the universal appeal of art to meet the public at all levels of understanding.” He adds that people generally understand that if future power is generated close to where it is used, then these devices might have to blend esthetically into the urban landscape.

Visit the original post at: Wind Power News

The next generation in wind power asset management

Wind operators must squeeze out every watt they can when the wind is blowing. To do so, wind projects must be reliable and maintained with minimum cost. With variable winds, high costs, and slim margins, everything has to work right to make sure that wind is attractive alternative power and a sound economic investment. So if a turbine is to work 20 years or more before retiring, it better be properly designed and maintained.

Standard procedures: not working

Most wind turbines are maintained by a combination of traditional schedule-based preventive maintenance and threshold-based alarm systems. A problem with scheduled maintenance is that the standard six-month interval between inspections may be too long to detect an emerging problem. And fixed-threshold alerts, typically set by OEMs, activate too late to support proactive maintenance. That’s because the alerts are intended to protect equipment from catastrophic damage and can’t take into account a wide range of normal wind-turbine operating conditions and unit-to-unit manufacturing variances. As a result, typical fixed-threshold-alert systems do not detect problems until after a failure occurs.

Likewise, traditional condition-monitoring and predictive maintenance tools, such as vibration analysis, oil analysis, and thermography, are limited because of the difficulty in accessing the typical wind-turbine nacelle, the variable nature of the machine, and the time limitations and analytic capabilities of the technicians using them.

Ideally, equipment maintenance should only be performed when something needs fixing. Most preventive maintenance works on the idea of regularly inspecting or servicing equipment to address potential failures before they progress. However, given the huge variations in operating profile and environment, it’s easy to see that the regular, fixed inspection interval of traditional preventive maintenance may not catch critical emerging problems in the wind environment.

The conventional power industry, however, leads the industrial world in predicting impending equipment problems before they occur. And it is doing so using a technique directly applicable to the wind industry. In fact, several wind companies, Invenergy in Chicago for one, already uses the technology to get early warnings, avoid surprises, and improve control of their operations. The industry reduces risk exposed by existing condition-monitoring tools by leveraging its SCADA data to remotely detect emerging problems in a method is called predictive analytics.

Briefly, the technology precisely identifies impending problems by detecting subtle changes in equipment operation. It has found problems earlier than OEMs’ alerting systems or other condition monitoring approaches, and well within traditional alarm limits.

The Availability and Performance Center at SmartSignal’s headquarters near Chicago use predictive analytics to monitor a range of plants and equipment, wind farms among them. Invenergy’s U.S. fleet of 975 GE 1.5 MW turbines are monitored this way.

A predictive analytics primer

It’s a real-time system that works by analyzing SCADA data once every 5 to 10 minutes. The data for a turbine includes its power output, wind speed, rotor rpm, lube temperatures, and so on. Predictive analytics compares real-time data to a software model of equipment when operation in good condition, and compensates for normal variations due to load and ambient conditions. Further, the method uses software models customized for individual pieces of equipment to provide the earliest possible warning of emerging problems. It readily integrates with an existing data infrastructure and it’s quick and easy to deploy, maintain, and use.

The method needs no new sensor and analysts need not review masses of SCADA data. Instead, the software analyzes data and alerts analysts only when it detects an exception, providing ample time to plan and respond. And, by using algorithms to identify pattern changes, the analysis is highly accurate.

For wind applications, the software uses models customized for each individual turbine, which considers for fluctuations in wind speed, direction, and ambient conditions. In real time, the software compares data collected in the nacelle to the model–literally tens of thousands of data points every 5 to10 minutes across a fleet–and notifies maintenance and engineering of impending problems. Owners then focus on fixing problems early, before catastrophic damage occurs.

Take a gearbox for example. During the initial system configuration, a gearbox model would be “trained” using representative data provided from a data historian such as OSI PI (a data historian is a database for storing time-series data from instrumentation). Typically, one year of data would be used to train the model. In live operation, data from relevant sensors on the gearbox, such as for vibration and temperatures, along with operational state information, such as power output and ambient temperature, would be compared to the model. It would then provide an “estimate” of what each value such be, based on how it was trained from the historical data. If the actual value statistically differs from the model estimate, the system generates an alert. Technicians would review the sensors in alert and develop a preliminary diagnosis of the problem. A next step would typically be further on-machine investigation or use of other techniques, such as oil sampling.

Best practices

Given the high capital intensity of the wind-power business, reliable, long-term operation of the equipment is critical for generating positive returns and continued industry growth. It won’t take many major equipment failures before the long-term profitability of a farm is lost. As assets age, performing major work only when needed will be critical to maintaining economic viability.

Remote monitoring and condition-based maintenance approaches will be required to maintain financial returns because wind turbines are hard to access and don’t receive the same “walk-around” monitoring typical of industrial plants. Although wind has unique characteristics, wind turbines are just another kind of machine and successful operators will take advantage of best practices from other industries to outstrip their competition.

Visit the original post at: Wind Power News

The next generation in wind power asset management

Wind operators must squeeze out every watt they can when the wind is blowing. To do so, wind projects must be reliable and maintained with minimum cost. With variable winds, high costs, and slim margins, everything has to work right to make sure that wind is attractive alternative power and a sound economic investment. So if a turbine is to work 20 years or more before retiring, it better be properly designed and maintained.

Standard procedures: not working

Most wind turbines are maintained by a combination of traditional schedule-based preventive maintenance and threshold-based alarm systems. A problem with scheduled maintenance is that the standard six-month interval between inspections may be too long to detect an emerging problem. And fixed-threshold alerts, typically set by OEMs, activate too late to support proactive maintenance. That’s because the alerts are intended to protect equipment from catastrophic damage and can’t take into account a wide range of normal wind-turbine operating conditions and unit-to-unit manufacturing variances. As a result, typical fixed-threshold-alert systems do not detect problems until after a failure occurs.

Likewise, traditional condition-monitoring and predictive maintenance tools, such as vibration analysis, oil analysis, and thermography, are limited because of the difficulty in accessing the typical wind-turbine nacelle, the variable nature of the machine, and the time limitations and analytic capabilities of the technicians using them.

Ideally, equipment maintenance should only be performed when something needs fixing. Most preventive maintenance works on the idea of regularly inspecting or servicing equipment to address potential failures before they progress. However, given the huge variations in operating profile and environment, it’s easy to see that the regular, fixed inspection interval of traditional preventive maintenance may not catch critical emerging problems in the wind environment.

The conventional power industry, however, leads the industrial world in predicting impending equipment problems before they occur. And it is doing so using a technique directly applicable to the wind industry. In fact, several wind companies, Invenergy in Chicago for one, already uses the technology to get early warnings, avoid surprises, and improve control of their operations. The industry reduces risk exposed by existing condition-monitoring tools by leveraging its SCADA data to remotely detect emerging problems in a method is called predictive analytics.

Briefly, the technology precisely identifies impending problems by detecting subtle changes in equipment operation. It has found problems earlier than OEMs’ alerting systems or other condition monitoring approaches, and well within traditional alarm limits.

The Availability and Performance Center at SmartSignal’s headquarters near Chicago use predictive analytics to monitor a range of plants and equipment, wind farms among them. Invenergy’s U.S. fleet of 975 GE 1.5 MW turbines are monitored this way.

A predictive analytics primer

It’s a real-time system that works by analyzing SCADA data once every 5 to 10 minutes. The data for a turbine includes its power output, wind speed, rotor rpm, lube temperatures, and so on. Predictive analytics compares real-time data to a software model of equipment when operation in good condition, and compensates for normal variations due to load and ambient conditions. Further, the method uses software models customized for individual pieces of equipment to provide the earliest possible warning of emerging problems. It readily integrates with an existing data infrastructure and it’s quick and easy to deploy, maintain, and use.

The method needs no new sensor and analysts need not review masses of SCADA data. Instead, the software analyzes data and alerts analysts only when it detects an exception, providing ample time to plan and respond. And, by using algorithms to identify pattern changes, the analysis is highly accurate.

For wind applications, the software uses models customized for each individual turbine, which considers for fluctuations in wind speed, direction, and ambient conditions. In real time, the software compares data collected in the nacelle to the model–literally tens of thousands of data points every 5 to10 minutes across a fleet–and notifies maintenance and engineering of impending problems. Owners then focus on fixing problems early, before catastrophic damage occurs.

Take a gearbox for example. During the initial system configuration, a gearbox model would be “trained” using representative data provided from a data historian such as OSI PI (a data historian is a database for storing time-series data from instrumentation). Typically, one year of data would be used to train the model. In live operation, data from relevant sensors on the gearbox, such as for vibration and temperatures, along with operational state information, such as power output and ambient temperature, would be compared to the model. It would then provide an “estimate” of what each value such be, based on how it was trained from the historical data. If the actual value statistically differs from the model estimate, the system generates an alert. Technicians would review the sensors in alert and develop a preliminary diagnosis of the problem. A next step would typically be further on-machine investigation or use of other techniques, such as oil sampling.

Best practices

Given the high capital intensity of the wind-power business, reliable, long-term operation of the equipment is critical for generating positive returns and continued industry growth. It won’t take many major equipment failures before the long-term profitability of a farm is lost. As assets age, performing major work only when needed will be critical to maintaining economic viability.

Remote monitoring and condition-based maintenance approaches will be required to maintain financial returns because wind turbines are hard to access and don’t receive the same “walk-around” monitoring typical of industrial plants. Although wind has unique characteristics, wind turbines are just another kind of machine and successful operators will take advantage of best practices from other industries to outstrip their competition.

Visit the original post at: Wind Power News

The next generation in wind power asset management

Wind operators must squeeze out every watt they can when the wind is blowing. To do so, wind projects must be reliable and maintained with minimum cost. With variable winds, high costs, and slim margins, everything has to work right to make sure that wind is attractive alternative power and a sound economic investment. So if a turbine is to work 20 years or more before retiring, it better be properly designed and maintained.

Standard procedures: not working

Most wind turbines are maintained by a combination of traditional schedule-based preventive maintenance and threshold-based alarm systems. A problem with scheduled maintenance is that the standard six-month interval between inspections may be too long to detect an emerging problem. And fixed-threshold alerts, typically set by OEMs, activate too late to support proactive maintenance. That’s because the alerts are intended to protect equipment from catastrophic damage and can’t take into account a wide range of normal wind-turbine operating conditions and unit-to-unit manufacturing variances. As a result, typical fixed-threshold-alert systems do not detect problems until after a failure occurs.

Likewise, traditional condition-monitoring and predictive maintenance tools, such as vibration analysis, oil analysis, and thermography, are limited because of the difficulty in accessing the typical wind-turbine nacelle, the variable nature of the machine, and the time limitations and analytic capabilities of the technicians using them.

Ideally, equipment maintenance should only be performed when something needs fixing. Most preventive maintenance works on the idea of regularly inspecting or servicing equipment to address potential failures before they progress. However, given the huge variations in operating profile and environment, it’s easy to see that the regular, fixed inspection interval of traditional preventive maintenance may not catch critical emerging problems in the wind environment.

The conventional power industry, however, leads the industrial world in predicting impending equipment problems before they occur. And it is doing so using a technique directly applicable to the wind industry. In fact, several wind companies, Invenergy in Chicago for one, already uses the technology to get early warnings, avoid surprises, and improve control of their operations. The industry reduces risk exposed by existing condition-monitoring tools by leveraging its SCADA data to remotely detect emerging problems in a method is called predictive analytics.

Briefly, the technology precisely identifies impending problems by detecting subtle changes in equipment operation. It has found problems earlier than OEMs’ alerting systems or other condition monitoring approaches, and well within traditional alarm limits.

The Availability and Performance Center at SmartSignal’s headquarters near Chicago use predictive analytics to monitor a range of plants and equipment, wind farms among them. Invenergy’s U.S. fleet of 975 GE 1.5 MW turbines are monitored this way.

A predictive analytics primer

It’s a real-time system that works by analyzing SCADA data once every 5 to 10 minutes. The data for a turbine includes its power output, wind speed, rotor rpm, lube temperatures, and so on. Predictive analytics compares real-time data to a software model of equipment when operation in good condition, and compensates for normal variations due to load and ambient conditions. Further, the method uses software models customized for individual pieces of equipment to provide the earliest possible warning of emerging problems. It readily integrates with an existing data infrastructure and it’s quick and easy to deploy, maintain, and use.

The method needs no new sensor and analysts need not review masses of SCADA data. Instead, the software analyzes data and alerts analysts only when it detects an exception, providing ample time to plan and respond. And, by using algorithms to identify pattern changes, the analysis is highly accurate.

For wind applications, the software uses models customized for each individual turbine, which considers for fluctuations in wind speed, direction, and ambient conditions. In real time, the software compares data collected in the nacelle to the model–literally tens of thousands of data points every 5 to10 minutes across a fleet–and notifies maintenance and engineering of impending problems. Owners then focus on fixing problems early, before catastrophic damage occurs.

Take a gearbox for example. During the initial system configuration, a gearbox model would be “trained” using representative data provided from a data historian such as OSI PI (a data historian is a database for storing time-series data from instrumentation). Typically, one year of data would be used to train the model. In live operation, data from relevant sensors on the gearbox, such as for vibration and temperatures, along with operational state information, such as power output and ambient temperature, would be compared to the model. It would then provide an “estimate” of what each value such be, based on how it was trained from the historical data. If the actual value statistically differs from the model estimate, the system generates an alert. Technicians would review the sensors in alert and develop a preliminary diagnosis of the problem. A next step would typically be further on-machine investigation or use of other techniques, such as oil sampling.

Best practices

Given the high capital intensity of the wind-power business, reliable, long-term operation of the equipment is critical for generating positive returns and continued industry growth. It won’t take many major equipment failures before the long-term profitability of a farm is lost. As assets age, performing major work only when needed will be critical to maintaining economic viability.

Remote monitoring and condition-based maintenance approaches will be required to maintain financial returns because wind turbines are hard to access and don’t receive the same “walk-around” monitoring typical of industrial plants. Although wind has unique characteristics, wind turbines are just another kind of machine and successful operators will take advantage of best practices from other industries to outstrip their competition.

Visit the original post at: Wind Power News

ReneSola to Report Fourth Quarter and Full Year 2009 Results on March 10, 2010
JIASHAN, China, Feb. 5 /PRNewswire-Asia-FirstCall/ — ReneSola Ltd (“ReneSola” or the “Company”) (NYSE: SOL) (AIM: SOLA), a leading global manufacturer of solar wafers, today announced that it will report its unaudited financial results for the fourth quarter and full year ended December 31, 2009 before the U.S. markets open on Wednesday, March 10, 2010.

ReneSola’s management will host an earnings conference call on Wednesday, March 10, 2010 at 8 am U.S. Eastern Standard Time / 9 pm Beijing/Hong Kong time / 1 pm Greenwich Mean Time.

Dial-in details for the earnings conference call are as follows:

U.S. / International: +1-617-614-3473
United Kingdom: +44-207-365-8426
Hong Kong: +852-3002-1672

Please dial in 10 minutes before the call is scheduled to begin and provide the passcode to join the call. The passcode is “ReneSola Call.”

A replay of the conference call may be accessed by phone at the following number until March 17, 2010:

International: +1-617-801-6888

Passcode: 81970616

Additionally, a live and archived webcast of the conference call will be available on the Investor Relations section of ReneSola’s website at http://www.renesola.com

Visit the original post at: Solar Power News

Aaron’s, Inc. to Donate Solar-Powered Electric Systems to Haiti Relief Efforts
ATLANTA, Feb. 5 /PRNewswire-FirstCall/ — Aaron’s, Inc. (NYSE: AAN) will donate two solar-powered electric systems, arriving in Haiti today and valued at $100,000, in support of Haiti relief efforts through ACORP, Aaron’s Community Outreach Program. Through ACORP, Aaron’s associates have donated thousands of hours of associate time to community service projects in more than 1,700 cities across the U.S. and $6.8 million in goods and services donations.

The solar-powered systems, designed by Sundance Solar Designs, LLC, will provide enough power to sustain two medical centers and 34 treatment tents. According to Spencer Smith, the Aaron’s franchise owner heading up the project with Sundance Solar, the lack of fuel to run generators in Haiti already has created a significant issue for medical professionals trying to administer treatment. Smith, a franchise owner of 21 Aaron’s stores, and his employees, donated $50,000 while Aaron’s, Inc. corporately donated an additional $50,000 through the ACORP program.

“American companies and individuals have offered support to Haiti on a massive scale, and Aaron’s is proud to be a part of that effort,” said Ken Butler, Aaron’s, Inc. Chief Operating Officer. “However, it was important that Aaron’s not just write a check, but give in a way that would create immediate impact. With these generators, thousands will receive critical medical treatment that we hope will make a life-saving difference for many Haitians.”

Sundance Solar Designs will donate their time, expertise, and purchase of the equipment as well as personally delivering and installing the systems in Haiti. Sundance Solar Design’s support team will arrive in Haiti today to ensure the generators are installed successfully. In addition to the solar panels that power the invertors and battery banks, Sundance Solar will bring the lighting fixtures and refrigeration units.

“With the donation of these solar-powered systems, we are addressing a specific and immediate need,” Spencer Smith said. “Without the fuel to run their generators, medical staff is forced to stop operating with the absence of light after the sun goes down. These unique solar-powered systems are self-sustaining and will not only provide lighting 24/7 for two full medical centers, doubling the hours available to treat patients, but will also run the refrigeration units containing life-saving medical supplies.”

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