The EPA says its solar and wind decision trees are available to help state and local governments and landowners to identify feasible sites for renewable energy. This may be a bit surprising, but some of the best areas for renewables are on contaminated sites, about 490,000 covering almost 15 million acres across the U.S. according to the EPA. The ability to reuse this land could have great economic and environmental benefits.

The EPA offers various other tools for the private solar sector, as well as resources such as podcasts, data, interactive maps and more. Check them all out on http://www.epa.gov/renewableenergyland/

Windpower Engineering & Development

As wind-turbine manufacturers seek additional ways to reduce costs and improve performance, greater focus has turned to improving modeling techniques as a way to reliably predict wind-turbine behavior prior to expensive prototyping and testing. In particular, better-designed wind-turbine blades are more effective and they create significant savings for the tower and drive train, major components in the overall system. In this regard, they reduce the initial and operation costs of the entire system, increasing overall competitiveness.

A wind turbine blade as modeled in VABS appears in the Siemens NX8 CAD user interface.

Originating in the aerospace industry for composite helicopter rotor blades, VABS software recently gained the attention of the wind industry for its capabilities in realistic modeling of wind-turbine blades. The program offers users a powerful, general-purpose cross-sectional analysis tool to calculate sectional properties, including structural properties (tension center and neutral axis, centroid, elastic axis and shear center, shear correction factors, extensional/torsional/coupling/bending/shearing stiffness, principal bending axes pitch angle, modulus weighted radius of gyration) and inertia properties (center of mass and gravity, mass per unit span, mass moments of inertia, principal inertia axes pitch angle, mass weighted radius of gyration). Using VABS for efficient, high-fidelity design and analysis, two to three orders of magnitude in computing time can be slashed relative to 3D FEA analyses, and without a loss of accuracy.

Available from AnalySwift, VABS, which now in version 3.6, implements various beam theories based on the concept of simplifying the original nonlinear 3D analysis of slender structures into a 1D nonlinear beam analysis using a powerful mathematical method, the variational asymptotic method. VABS models structures for which one dimension is much larger than the other two (i.e., a beam-like body), even if the structures are made of composite materials and have a complex internal structure. It takes a finite-element mesh of the cross section including all the details of geometry and material as inputs to calculate the sectional properties, including structural properties and inertial properties. These properties are needed for the 1D beam analysis to predict the global behavior of the slender structure. The 3D pointwise displacement, strain, and stress distribution within the structure can also be recovered based on the global behavior of the 1D beam analysis.

Enabled by VABS, analysis can be done as efficiently and simply as conventional beam analysis, without losing accuracy compared to more complex and time-consuming 3D FEA. Users can confidently design and analyze real structures with complex microstructures due to this unique, efficient, high-fidelity feature of VABS. For example, structures as complex as real composite rotor blades with hundreds of layers can be easily handled by a laptop computer.

The screen shot is of the NX 8 interface.

VABS is implemented using finite element techniques with a general element library that includes all the typical 2D elements such as 3, 4, 5, 6-noded triangular elements and 4, 5, 6, 7, 8, 9-noded quadrilateral elements. Users are free to choose the type of elements, and different types of elements can be mixed within one mesh, if necessary. This flexibility lets VABS model beams of any shape.

The program can also deal with arbitrary layups. For instance, users can provide one parameter for the layup orientation and one parameter for the ply orientation to uniquely specify the material system in a global coordinate system. Nine parameters can be used for the ply orientation when a ply is highly curved and the ply angle is not uniform within an element.

There is no requirement that the beam reference line be the locus of cross-sectional area centroids. VABS can calculate the centroid for any arbitrary cross section, and users can choose their own reference line for the convenience of the 1D global beam analysis. Furthermore, it can deal with isotropic, orthotropic, and general anisotropic materials.

According to Dr. Dewey Hodges, an expert in rotorblade modeling and FEM, and Senior Advisor to AnalySwift, “Because VABS is based on an asymptotic approximation of 3D nonlinear anisotropic elasticity, for a comparable set of variables it will always give results that are at least as good as the best engineering approach to beam modeling.”

A design-driven preprocessing program, PreVABS, generates high-resolution finite element modeling data for VABS. It can model sophisticated cross-section configurations for various composite blades. It also significantly reduces intensive modeling efforts for generating 3D FEA models, which is either time consuming or impractical, especially during the preliminary and intermediate design phases.

Commercialized by AnalySwift, VABS was originally developed at Georgia Tech and later significantly enhanced at Utah State University. Developers, users, and academic publications have extensively verified its accuracy, with continuous development spanning over 20 years. Several wind-turbine manufacturers, national labs, U.S. Army, and others are using VABS. Evaluation licenses of VABS and PreVABS are available at no cost through AnalySwift.

The program can be quickly and conveniently integrated into other environments such as computer-aided design software, multidisciplinary optimization environments, or commercial finite-element packages. Additionally, a VABS interface for the widely used Siemens NX Advanced FEM software is now available from MAYA HTT.

AnalySwift LLC
www.AnalySwift.com

Windpower Engineering & Development

The setup shows the model turbine in the wind tunnel at the University of Milan. Bachmann M1 Automation System provides controls and data logging.

The aerospace-engineering department at Politecnico di Milano (Italy) is working on a model wind turbine in the school’s wind tunnel. It has been used for researching operating behaviors in extreme conditions. Bachmann electronic is providing the controller for the model.

The setup is to test an aero-servo-elastic model that can provide information about the behavior of wind turbines in high winds. Information about the aerodynamics and aeroelasticity of the wind turbine is collected for conditions that are not easily tested in the field.

The turbine model features active individual blade pitch and torque controls. To obtain more realistic simulations, the tower and rotor blades must behave as elastic materials. The wind turbine model is equipped with a large number of sensors to record extensive data.

Bachmann electronic cooperates with universities and research institutes because their research results influence future developments. Prof. Carlo L. Bottasso from the Department of Aerospace Engineering at the school is delighted: “The Bachmann M1 automation system lets us simulate the realistic operation of the wind turbine in the wind tunnel.”

Bachmann Electronics
http://www.windpowerengineering.com/directory/?s=Bachmann&searchsubmit=Search

Windpower Engineering & Development

This really cool wind map from a pair of Google computer scientists may hold the answer. One can view the pathways of wind across the U.S. live. Information is updated hourly from the National Weather Service’s forecast database. I notice many times winds are blowing across the Great Lakes from Ohio toward Pennsylvania. Now the weather patterns make sense!

I also like how the map shows wind as white and grey strands, indicating speed as well.  Glad I’m not Nebraska right now! Check it out here.

Windpower Engineering & Development

The annual capacity factor for the downdraft portion of the Energy Tower is predicted at about 51%.

The Downdraft Tower is a tall hollow cylinder with a water spray system at the top. Pumps deliver water to the top of the tower to spray a fine mist across the entire opening. The water evaporates and cools the hot dry air at the top. The cooled air is denser and heavier than the outside warmer air so it falls through the cylinder at speeds up to and in excess of 50 mph, driving rotors at the base of the structure. The rotors power generators to produce electricity.
In areas where atmospheric conditions are conducive, the exterior of the Downdraft Tower may be constructed with vertical “wind vanes” that capture the prevailing wind and channel it to produce supplemental electrical power. This dual renewable energy resource enhances the capability and productivity of the Clean Wind system.

The developer says the tower can operate without consuming a fuel or producing waste. The technology has potential to generate clean, cost effective, and efficient electrical power without the damaging effects caused by using fossil or nuclear fuels, and other conventional power sources. The Company also believes that increasing emphasis on green technologies and governmental incentives in the energy industry should have a positive long-term effect on the Company’s planned business and the wind energy industry in general.

The developer anticipates that each tower will be capable of generating up to 2,500 MW per hour, gross, of which about 1/3 will be used to power its operations. From normal to ideal circumstances the Tower should have a potential yield of 1,100 to 1,500 MW/h available for sale to the power grid. At this writing, avoided costs per kilowatt in California are running approximately $0.11/kWh.

The annual capacity factor for the downdraft portion of the Energy Tower is predicted at approximately 51%. Prime production periods are daytime and evening during spring, summer and fall, which closely align with electricity demand patterns. However, the External Wind Capture keeps working 24/7, whenever a wind is blowing, including cold winter months and at night. Its capacity factor is estimated at about 75%, which raises the Energy Tower’s overall capacity factor to above 60%.

The Downdraft Tower will be constructed using conventional materials, equipment and techniques, so associated industries surrounding each tower site will benefit from the creation of professional jobs, manufacturing, construction, and transportation jobs.

The Clean Wind Energy downdraft tower is a U.S. based invention that will provide clean renewable energy at a cost more favorable than nuclear plants with no negative impacts to our planet.

Clean Wind Energy Tower
cleanwindenergy.com

Windpower Engineering & Development

The red plot on a turbine-power curve tells that the turbine in its ramp section is underperforming compared to the wind project average (black). Is lightning the cause of the underperformance?

Lightning strikes to wind-turbine generators cause significant damage each year. Blades are particularly vulnerable, leading to turbine and wind projects underperformance. Lightning also increases the risk of future turbine component failure due to residual affects that may take a turbine offline for an extensive period. Thus, it is important that operators quickly identify turbines that have suffered a strike to reduce the probability of further losses and damage.

Inspecting each turbine on a large wind farm would take too much time and effort due to the sheer number installed. But knowing the location (±150 meters), timing (time stamp), and strength (peak current) of a lightning strike greatly eases underperformance investigations and shortens repair time. Additionally, this information can serve as critical evidence with regard to replacement warranty parts.

Software can help operators verify and locate recent and historical lightning events, which they can then correlate with the damaged assets. A program called Fault Analysis and Lightning Location System (FALLS), developed by Vaisala, lets utilities and wind farm operators analyze lightning events in near-real time and access historical lightning data for analyzing past exposure of wind farms and transmission assets to lightning.

FALLS software has three main applications: asset-exposure studies, asset-reliability studies, and lightning-strike density studies. A particular focus depends on the kind of data an operation is looking for. Asset exposure studies are used to overlay infrastructure with the correlative lightning activity when the exact time of the damage is unknown. It is used proactively to determine which generators had the highest risk or potential of being affected during a recent storm. Operators don’t want to find out months or even years later that their power generation has been reduced due to lightning–they want to know right away. In the U.S., the software uses lightning data from the National Lightning Detection Network (NLDN), owned and operated by Vaisala. The NLDN can provide the current intensity of a lightning event, its duration, timing to the millisecond, and a median location accuracy better than 250m. This data can greatly increase chances of determining exactly which turbines were affected and how critical the damage may be.

The density study map was generated by the NLDN network.

Asset-reliability studies are used for event-specific lightning analysis in near real-time. These two FALLS studies let operators locate poorly performing turbines, validate lightning protection design, and correlate faults to lightning activity (or a lack of lightning activity). The IEC standard for wind-turbine lightning protection of wind turbines assumes that all strokes in a collection area strike a wind turbine. The collection area is a circle centered on the turbine with a radius equal to three times the tip height. Data from FALLS can help determine when a damage event occurred, as well as which stroke best matches the fault timing, and which stroke had the highest peak current event, likely causing the most damage. The software lets operators more accurately pin-point which turbines are affected, thereby improving the overall efficiency of the operation.

Lightning data from FALLS software indicates strength and location of strokes.

Density studies are used to access the history of a site’s exposure to lightning. This may be where an analysis of “hot spots” is needed for lightning activity in or around a wind farm, say over a three to five-year period. Accessing historical lightning data, the software lets users conduct an investment study and determine the lightning density per square kilometer within the area of interest. The software displays the lightning events on a map by date, kA (strength in kilo-amperes) or discrimination (lightning type and polarity) to more easily view the data. This lets users better plan for the vulnerability of turbines and know the areas with the highest concentration of lightning.

There is no way to avoid lightning strikes to a wind turbine. There are, however, ways to quickly determine whether or not lightning was the cause of a problem, and react accordingly to best manage the situation. Tools, such as lightning software, and networks such as NLDN, help verify and plan for lightning strikes so that electric utilities and wind-farm operators can efficiently continue to offer cost-effective and reliable renewable power. WPE

By: Melanie Scott, Meteorologist at Vaisala www.vaisala.com

Windpower Engineering & Development

The map, from 3TIER, shows departures from long-term mean wind speeds that range from -20% to +20% and provides an indication of how wind projects should have performed relative to their long-term production average based on their location. This type of analysis enables financiers and owners to perform portfolio analysis across regions and quickly view the effects of weather anomalies on both existing and proposed investments.

For the year as a whole, the US experienced above average wind speeds, though month-to-month and regional variability were not uniformly above average across the country. The Pacific Northwest and New England saw wind speeds roughly 5% below average for the year, while a broad section of the US from northern Montana to Texas and the mid-Atlantic states enjoyed a strong wind year with wind speeds 5-15% above normal.

The year began with weak La Niña conditions and lackluster wind speeds. However, a stronger La Niña, which occurred later than initially forecasted, combined with a negative Pacific/North America (PNA) pattern led to increased wind speeds throughout the spring. Summer winds were particularly strong in the southern states, where warm and dry conditions continued under a large upper-level ridge that suppressed winds further north. The ridge persisted into September, when the central and eastern US moved back into a more vigorous weather pattern, with frequent frontal passages contributing to higher than normal wind speeds.

By the end of 2011 the North Atlantic Oscillation (NAO) was in a positive phase, associated with lower than normal winds in the western US. The effects of this trend dominated those of the persistent La Niña state in the equatorial Pacific. However, winds were above normal for most of the country east of the Rocky Mountains, except in the northeastern US, where upper-level ridging kept temperatures warm and wind speeds low.

The wind performance map was created by comparing output from 3TIER’s continually updated meteorological dataset with wind conditions averaged over the period 1969-2008 from the same dataset. Wind speed values were computed using a numerical weather prediction (NWP) model run at a 15 km resolution and adjusted using available observations. The underlying datasets for 3TIER’s wind performance maps provide clients with operational intelligence for every location within a region and are available in nearly all regions worldwide.

Windpower Engineering & Development

Transformers serve as a hub for collection and distribution of energy changing the voltage level at different locations of the grid. They are a key component of the Smart Grid, loosely defined as an automated, widely distributed energy delivery network, characterized by a two-way flow of electricity and information, and capable of monitoring everything from power plants to customer preferences to individual appliances.

There is some ways to go before the vision of the Smart Grid is realized, but recently monitoring transformers has taken a leap forward, as energy production sites seek solutions to lower maintenance costs. Remote monitoring is seeing increasingly wider use especially remote wind farms and solar-powered production sites where having someone present to monitor transformers at fixed intervals is a costly proposition. As more renewable energy production sites come online, utilities have been investing in monitoring technology that keeps labor costs to a minimum.

Predictive maintenance gains favor over preventive

Remote monitoring and communication capabilities let utilities conduct “predictive” maintenance of transformers, which means conducting maintenance only when a parameter starts deviating from a pre-set standard. This typically does not occur at a pre-determined interval. Remote management let operators“see” how a transformer is operating and send someone to fix it only when it’s necessary.

The schematic show how Visizmax would network a wind farm for predictive maintenance.

Daniel Lambert, of Vizimax, a Montreal, Canada-based company that offers remote monitoring and control systems for public utilities and the industrial and private sectors, notes that remote management is being widely embraced, especially as operators need more profitable maintenance functions. “It is similar to today’s cars that tell you when to change your oil or conduct other maintenance based on specific driving habits,” said Lambert. “Rather than changing your oil at 6,000 mile intervals, electronic sensors can determine if you do mainly city or highway driving and signal the need for an oil change accordingly. That basic principle has been adapted for use in monitoring transformers.”

When maintenance is done purely in preventive mode, operators have no idea what is really happening inside and next to the transformer, and may tend to unnecessarily shorten intervals between each maintenance activity. With predictive monitoring, utilities can save money by having a real understanding of the key transformer parameters, which include temperature, liquid level, pressure vacuum, outgoing voltage, and ingoing voltage.

Utilities that conduct preventive maintenance programs usually use either time or quantity of energy consumed as the determining factor. Once they install remote monitoring capabilities, most switch to predictive-maintenance modes. Payback on the investment in remote monitoring equipment is estimated between 9 and 15 months.

Among those moving in the direction of this type of remote monitoring are GE, Siemens, Alstom Grid (Areva T&D), Schneider Electric, BHEL, Crompton Greaves, New York Power Authority, National Grid, Power Grid of India, and Hydro-Quebec, among others.

Building transformers that incorporate digital monitoring

Many transformer manufacturers are recognizing this growing demand for online transformer monitoring products and diagnostic services, and investing in building them, especially for step-up transmission, high-voltage transformers.

These technologies will be critical for improving grid reliability and helping utilities avoid transformer failures and resultant blackouts. They will also reduce maintenance costs and defer capital expenditures by extending a transformer’s useful life.

In addition to monitoring vital statistics such as temperature, pressure, and vacuum levels, there has also been a burgeoning interest in conducting dissolved gas analysis (DGA) of the oil in transformers. A DGA takes samples of an oil’s exhaust gases to determine if events have occurred that might be detrimental to the transformer and reduce its life. Industrial transformer maintenance people and utilities are setting up these planned sampling programs, using online devices that can monitor oil quality.

This can greatly improve reliability, because users will know in advance when something has to be replaced, rather than risk unscheduled outages. For food-processing plants and mills, which can lose millions of dollars when power is interrupted, this type of sampling program is being undertaken to ensure reliable power.

Transformers in place now are already using various smart devices for load switching. In the 21st century, the move will be towards monitoring systems that promote transformer reliability. Ensuring reliability on the grid by replacing equipment before it fails and anticipating upcoming problems is what transformer manufacturers will be focusing on.

Remote monitoring equipment

The latest technology used for remote transformer monitoring includes a combination of a remote terminal unit, a programmable language controller, a gateway (a network node equipped for interfacing with another network that uses different protocols), and a protocol converter. The complete monitoring system is usually placed in service by a system integrator or a power manufacturer.

One type of control panel can show the essentials for each turbine. Why is #2 not producing?

An example of one such system is Vizimax’s RightWON, a secure, modular, rugged automation remote terminal unit (RTU), programmable logic controller (PLC), gateway, communication conversion protocol platform that connects circuit breakers, transformers, IEDs, meters, sensors, control and monitoring devices at the substation level or anywhere on the distribution network. In addition to energy applications, the monitoring devices are used in water and telecommunications monitoring.

The unit is for remote management applications, providing support for equipment through its data acquisition, monitoring, control and remote maintenance functions. At renewable energy sites, the system shuts down and locks circuit breakers (CBs) and inverters remotely, which avoids traveling to an energy-production site for distribution-line maintenance. The production site is still operational while maintenance is occurring on the network.

The unit is often used in substations, where it usually connects to transformers, circuit breakers, intelligent electronic devices (IEDs), protective relays, and meters through the electric utility’s private network. In some instances, in can be used strictly for monitoring transformers in substations, using wireless connectivity (through GSM, GPRS, 3G or CDMA networks). Parameters such as temperature, liquid level, pressure vacuum, outgoing voltage, and ingoing voltage will be measured and transferred to a utility’s supervisory control and data acquisition (SCADA) system. Wireless monitoring calls for specialized Web service interfaces.

The system makes it economical to conduct monitoring, because it can convert older controls and sensors already implemented to newer communication protocols without having to replice or modify them. The monitoring system connects to the SCADA using fiber optic cables or web interface through a wireless device. It offers a remote and local view on event logs charting key assets status changes and alarm signals about exceeding thresholds.

Remote access is made possible through networking, security, and telecommunication functions, and is supported by a broad range of integrated interfaces. These interfaces support a wide variety of industrial protocols (IEC 61850, DNP3, ModBus, and IEC 60870) as well as Web access and remote maintenance functions. The information collected is easily viewed on smart phones from anywhere, any time. The system supports sending notifications by email, text messages, or pager. Users who receive a message can access the system using a Web browser to view the data and operate the site remotely.

The system is IEC 61850 KEMA certified and can also be used for a variety of other Smart Grid applications, including remote default detection and automated reclose/disconnect operations within distribution networks, and alarms and operational data broadcast and commands, usually to or from the SCADA of power utilities, IPPs, integrators and equipment manufacturers’ team management applications.

Monitoring equipment also used in re-energizing transformers

In addition, new flux management monitoring technology is being deployed more at the end of transmission lines during re-energizing a transformer, a regular process that takes place every time a production site connects to the grid. The need to re-energize varies considerably, but there are always times when required maintenance requires stopping the connection between the production site and transmission lines. When maintenance is completed, the transformer must be re-energized.

The flux management units avoid network inrush that may create network outages while transformers are re-energized, something that in the past had been a frequent occurrence. This is extremely important, because several hours of lost revenue in a month can mean the difference between a profitable energy production site and an unprofitable one.

The system calculates the residual flux while a transformer is reenergized at the last operation, and ensures that the next transformer operation is performed at the exact millisecond such that residual flux is identical to the previous operation, which minimizes current inrush and stress on both the high voltage transformer and circuit breaker.

The unit measures relevant parameters from the transformer and sends a command to the circuit breaker of the transformer to achieve this operation. Using this equipment increases the quality of the network, decreases network outages, and decreases the frequency and the cost of maintenance operations.

Last thoughts

Remote monitoring makes it possible to manage maintenance of remote power equipment in the field in a predictive mode instead of the more traditional and more expensive preemptive or preventive mode. By remotely monitoring power equipment in remote locations, electric utilities now only must execute maintenance operations on their equipment when it is required. This is going a long way to cutting costs for the many renewable energy production sites that are coming online.

Pacific Crest Transformers
http://www.pacificcoasttransformers.com

Windpower Engineering & Development

The GLD360 is now able to locate and characterize lightning in areas of the world where meteorological observations may be partially lacking or absent.

The developer of a global lightning detection network will provide access to its Global Lightning Dataset GLD360, which holds lightning data with peak current estimates, greater location accuracy, and improved polarity classification than previously available. The enhancements in data quality will help users make more informed decisions, increase operational safety and efficiency, and deliver better services.

Vaisala has implemented a new processing algorithm that lets the global network identify the location of a cloud-to-ground lightning stroke within a range of 2 to 5 km. Polarity classification accuracy now stands at better than 90%, while peak current estimates have been improved to be accurate within 25% of the peak current value. The GLD360 is the only global lightning dataset, say developers,  that provides polarity and peak current estimates for lightning events. “For the first time, quality lightning warnings are now possible on a global-scale,” says Nick Demetriades, Offering Portfolio Manager for Vaisala’s Airports business.

“The significant improvement in the GLD360 data quality is due to a vastly improved location accuracy of the global network, combined with its ability to detect about 70% of all cloud-to-ground lightning flashes. This will improve the safety and efficiency of airport operations across the world.”

According to the company, the global lightning-detection network provides uniform coverage with high detection efficiency over the entire world because it has more lightning information than any other comparable dataset in the world. Daily counts routinely exceeding 1.5 million events.

A density study from Vaisala tells where and frequency of lightning strikes.

The GLD360 is now able to locate and characterize lightning in areas of the world where meteorological observations may be partially lacking or absent. Data from the network is easily assimilated into weather models to improve short-to-medium term forecasts. In addition, it can be used as a proxy for weather-radar information in areas with limited or non-existent radar coverage. Because the company owns and operates the global network and delivers lightning data as a service, users can access the information in the GLD360 without having to make substantial hardware investments.

Vaisala Inc.
www.vaisala.com

Windpower Engineering & Development

Generation technologies such as wind and solar are gaining market share, while at the same time they are introducing an uncertain wrinkle into the old reliable power grid — variability.

This article comes from NREL
With the simple flick of a light switch, you connect to “the machine,” the North American electric grid. It’s the world’s most complex transmission and distribution system — also is referred to as the world’s largest machine. That same machine has run reliably on coal, natural gas, and nuclear energy for decades.

Now, it’s time for a tune up. Newer power-generation technologies, such as wind and solar are gaining market share, while at the same time, they introduce an uncertainty into the power grid in the form of variability.

The new Energy Systems Integration Facility (ESIF) at U.S. Department of Energy’s (DOE) National Renewable Energy Laboratory (NREL) is tackling the challenge of keeping the power grid running reliability while at the same time introducing a host of new equipment into an already complex system.

According to NREL’s director for Electricity Resources and Buildings Integration, David Mooney, the grid has operated essentially the same for more than 50 years. Utilities know how to predict energy demand by looking at the day of the week and the weather forecast. Then, utilities dispatch generating sources (usually from coal or natural gas) to meet expected demand.

An artist with the Smith Group, rendered the Energy Systems Integration Facility. The view is from west to east.

“It was a pretty orderly way to operate a system,” says Mooney. “Today, there are a lot of technologies coming online — including wind and solar — that are going to require a transformation in the way this orderly system operates. Now instead of only having variability in the electric demand, we are also introducing technologies that make the generating supply variable as well.”

Renewable Energy Already is Connected — Or Is It?

For homeowners with photovoltaics (PV) on their roofs, or the technician working a wind farm in Texas, this may seem moot. Their technologies already are connected to the grid and the electrons seem to be flowing seamlessly.

However, this type of renewable energy still make up a small fraction of the America’s overall energy generation. According to the latest data from the U.S. Energy Information Administration, power generation from renewables such as biomass, geothermal, solar, and wind have so far accounted for less than 5% of the total U.S. power generation in 2011.

Connecting that small amount of renewable energy into the power grid is not a big deal. “If you have 1,000 homes and five to 10% of those add solar, the variation and the output of the PV is in the noise of the grid,” says Mooney. “Right now, utilities view PV systems in small numbers as a demand reduction technology — no different than people switching to compact florescent bulbs. But, if 50% of those 1,000 homes have a PV system, then the output could start to look more like a generating technology to the utility. Once it reaches those kinds of numbers, the utility has to start worrying about things like variation in cloud cover that cause PV output to vary.”

“As all of these new technologies become cost effective, they are starting to get used a lot more and utilities ask, what’s the best way to integrate these variable technologies while maintaining a safe and reliable electric power system?” says NREL’s Director of Energy Systems Integration Ben Kroposki.

ESIF is the first significant DOE laboratory designed specifically to deal with the integration issue. NREL’s researchers will be able to configure electric systems the way they would appear in the field and operate them at the same level of power as the utility uses.

“We all know how we react when the power goes out. The local utility usually bears the brunt of the PR problems associated with an outage,” says Mooney. “So it is understandable that they are conservative in how they go about adopting new technology. That is why the ESIF is so important for reducing that risk. The utilities will be able to operate new technologies in an environment that mimics the real system so they can work out the bugs of introducing new technologies beforehand and maintain the high reliability standards that we have all come to expect.”

ESIF also will be a plug-and-play environment for industry. “ESIF is set up so that partners can bring in technologies — such as a PV inverter or battery system — and we will have on hand the other equipment that the technology being tested would connect to. They don’t have to go and try to find these complete systems,” Kroposki said.

ESIF also will loop the utilities’ hardware into a simulation environment so they can look at new technologies operating in a combination of real world, real power and simulated or virtual environments to see the impact that these new systems are going to have on the reliability and quality of the power. “Once they try it all out in the ESIF, we believe the utilities will be much more inclined to adopt the technology,” says Mooney.

Fun facts to know and tell about ESIF:

• Cost: $135 million
• Area: 182,500 ft²
• Office space: about  200 ft²
• State-of-the-art electric systems simulation and visualization
• Component and systems testing and at MW-scale power
• Combine functioning systems with utility simulations for real-time, real-power evaluation of high penetrations of renewable energy
• 15 laboratories
• Four outdoor test areas
• Construction complete: fall 2012

Other key service and support features:

• Research Electrical Distribution Bus (REDB)
• High Performance Computing Data Center (HPCDC)
• Hardware-in-the-Loop Prototyping at Megawatt-scale Power
• Collaboration and Visualization Rooms
• High bay control room

Another challenge for NREL researchers will include looking for ways to improve the grid. “For mostly economic reasons, we can’t build up a new grid and then switch over to it,” Mooney said. “ESIF will let us look at how we can make the grid ‘smarter’ and more flexible to receive technologies in a way that can maintain or even enhance the existing grid.”

Many technologies on the grid are antiquated, and can be up to 50 years old. A “smart grid” has three components that the current grid doesn’t have:

• Sensors as part of the grid so that power quality is measured in real time
• Communications to relay data coming from sensors to utility operators to assist with decision making
• Controls that allow system operation changes from a central location.

“People are surprised to learn that most utilities still don’t know about a power outage until they get a call from a customer,” Mooney said. “If we had a smarter grid, we would have sensors on transformers and power lines that would let utilities act preemptively if problems in power quality were arising so they could keep the power on. However, if the power did go out, utilities would be able to see it immediately and dispatch crews to minimize down time.”

As utilities put smarter technologies onto the grid, another avenue for energy savings is to have the grid communicate with a home energy-management devices so the home can work with a utility to manage power needs.

“The smart grid will offer the possibility of frequent, likely automated communication between a utility and a customer,” Mooney said. “As a consumer, you will likely be able to know when the power is cheapest, for example, and have a plan with the utility that tailors your power consumption accordingly.”

The foundations for a smarter grid are being laid today. In June 2011, Secretary of Energy Steven Chu announced that more than 5 million smart meters had been deployed thanks to Recovery Act-funded efforts to accelerate modernization of the nation’s electric grid.

“To compete in the global economy, we need a modern electricity grid,” he said. “An upgraded electricity grid will give consumers choices and promote energy savings, increase energy efficiency, and foster the growth of renewable-energy resources.”

NREL
www.NREL.gov

Windpower Engineering & Development