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  • richardmitnick 11:43 am on July 29, 2015 Permalink | Reply
    Tags: , Electricity,   

    From PNNL: “Power grid forecasting tool reduces costly errors” 


    PNNL Lab

    July 29, 2015
    Dawn Zimmerman

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    PNNL’s Power Grid Integrator has demonstrated up to a 50 percent improvement in forecasting future electricity needs over several commonly used tools. Project lead Luke Gosink, right, consults on the use of the new tool, which could save millions in wasted electricity costs.

    Accurately forecasting future electricity needs is tricky, with sudden weather changes and other variables impacting projections minute by minute. Errors can have grave repercussions, from blackouts to high market costs. Now, a new forecasting tool that delivers up to a 50 percent increase in accuracy and the potential to save millions in wasted energy costs has been developed by researchers at the Department of Energy’s Pacific Northwest National Laboratory.

    Performance of the tool, called the Power Model Integrator, was tested against five commonly used forecasting models processing a year’s worth of historical power system data.

    “For forecasts one-to-four hours out, we saw a 30-55 percent reduction in errors,” said Luke Gosink, a staff scientist and project lead at PNNL. “It was with longer-term forecasts — the most difficult to accurately make — where we found the tool actually performed best.”

    The advancement is featured this week as a best conference paper in the power system modeling and simulation session at the IEEE Power & Energy Society general meeting in Denver.

    A delicate balancing act

    Fluctuations in energy demand throughout the day, season and year along with weather events and increased use of intermittent renewable energy from the sun and wind all contribute to forecasting errors. Miscalculations can be costly, put stress on power generators and lead to instabilities in the power system.

    Grid coordinators have the daily challenge of forecasting the need for and scheduling exchanges of power to and from a number of neighboring entities. The sum of these future transactions, called the net interchange schedule, is submitted and committed to in advance. Accurate forecasting of the schedule is critical not only to grid stability, but a power purchaser’s bottom line.

    “Imagine the complexity for coordinators at regional transmission organizations who must accurately predict electricity needs for multiple entities across several states,” Gosink noted. “Our aim was to put better tools in their hands.”

    Five heads better than one

    Currently, forecasters rely on a combination of personal experience, historical data and often a preferred forecasting model. Each model tends to excel at capturing certain grid behavior characteristics, but not necessarily the whole picture. To address this gap, PNNL researchers theorized that they could develop a method to guide the selection of an ensemble of models with the ideal, collective set of attributes in response to what was occurring on the grid at any given moment.

    First, the team developed a statistical framework capable of guiding an iterative process to assemble, design, evaluate and optimize a collection of forecasting models. Researchers then used this patent-pending framework to evaluate and fine tune a set of five forecasting methods that together delivered optimal results.

    The resulting Power Model Integrator tool has the ability to adaptively combine the strengths of different forecasting models continuously and in real time to address a variety scenarios that impact electricity use, from peak periods during the day to seasonal swings. To do this, the tool accesses short- and long-term trends on the grid as well as the historical forecasting performance of the individual and combined models. Minute by minute, the system adapts to and accounts for this information to form the best aggregated forecast possible at any given time.

    “During these forecasting tasks, we noted that an ensemble of models, even those considered moderate performers, would routinely outperform individual, high-performing models,” Gosink said.

    Researchers used PNNL’s Institutional Computing resources to develop and validate the tool, making it possible to process a year’s worth of historical grid data within a few days. High-performance computing also made it possible to evaluate the tool’s performance across multiple forecasting periods, ranging from 15, 30 and 60 minutes up to four hours. However, the tool also runs on standard computer workstations commonly used by the electric industry.

    Flexibility in application

    “The underlying framework is very adaptable, so we envision using it to create other forecasting tools for electric industry use,” Gosink said. “We also are exploring other applications, from the prediction of chemical properties studied in computational chemistry applications to the identification of particles for high-energy physics experiments.”

    Initial development of the Power Model Integrator was funded by PNNL’s Future Power Grid Initiative and GridOPTICS.

    See the full article here.

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    Pacific Northwest National Laboratory (PNNL) is one of the United States Department of Energy National Laboratories, managed by the Department of Energy’s Office of Science. The main campus of the laboratory is in Richland, Washington.

    PNNL scientists conduct basic and applied research and development to strengthen U.S. scientific foundations for fundamental research and innovation; prevent and counter acts of terrorism through applied research in information analysis, cyber security, and the nonproliferation of weapons of mass destruction; increase the U.S. energy capacity and reduce dependence on imported oil; and reduce the effects of human activity on the environment. PNNL has been operated by Battelle Memorial Institute since 1965.

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  • richardmitnick 11:21 am on January 3, 2015 Permalink | Reply
    Tags: Electricity, Three Gorges Dam   

    From Discovery: “Three Gorges Dam Breaks Hydropower Record” 

    Discovery News
    Discovery News

    Jan 3, 2015
    by AFP

    China’s Three Gorges dam has broken the world record for annual hydroelectric power production, more than a decade after it became the world’s largest power plant, its operator said.

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    The dam in September 2009

    The Yangtze river power station generated 98.8 billion kilowatt-hours of electricity in 2014, the Three Gorges Dam Corporation said in a statement, topping the 2013 production from the Brazilian-Paraguayan Itaipu dam.

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    Itaipu Dam

    The amount of electricity generated by the Three Gorges plant is roughly equivalent to burning 49 million tons of coal, said Thursday’s statement, thereby preventing 100 million tons of carbon dioxide emissions.

    But concerns have been raised about the environmental and human cost of the huge project, which saw more than a million people moved before it opened around a decade ago.

    Thousands remain in poverty, and China’s government in 2012 made a rare admission that the treatment of migrants relocated for the dam was still an “urgent problem”.

    Campaign groups say it has damaged biodiversity, threatening the critically endangered Yangtze river dolphin.

    The Three Gorges dam is the world’s largest power plant by installed capacity with 22,500 megawatts, a third more than Itaipu, on the Parana river.

    See the full article here.

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  • richardmitnick 8:04 am on November 18, 2014 Permalink | Reply
    Tags: , Electricity, , ,   

    From phys.org: “Electrochemical cell converts waste heat into electricity” 

    physdotorg
    phys.org

    November 18, 2014
    Tessa Evans

    Picture a device that can produce electricity using nothing but the ambient heat around it. Thanks to research published in the Proceedings of the National Academy of Science today, this scenario is a step closer – a team from MIT has created an electrochemical cell which uses different temperatures to convert heat to electricity.

    The cell only needs low-grade waste heat – less than 100C – to charge batteries, and is a significant step forward compared to similar devices which either require an external circuit for charging or high temperature heat sources (300C).

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    Diagram depicting how energy is generated as temperature varied. Credit: Gang Chen, CC BY

    “It’s a great idea to be able to recover useful electrical energy from waste heat,” Anthony Vassallo, Delta Electricity Chair in Sustainable Energy Development at The University of Sydney, said.

    At higher temperatures (60C), the cell (which is made of Prussian blue nanoparticles and ferrocyanide) was charged, and following cooling to 15C, the cell discharged energy. At lower temperatures the cell discharged more energy than was used to charge it, so converted heat to electricity.

    The amount of heat energy generated is dependent on the temperature and the Carnot limit. The Carnot limit is the maximum absolute amount of heat energy that can be converted to useful electricity.

    In cars, engine heat efficiency has reached around 20%, while the Carnot limit – the absolute efficiency which could be reached at that operating temperature – is 37%

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    Credit: Tao Zero/Flickr, CC BY-NC-SA

    This means that most heat energy conversion is based on high temperature, and low-grade heat conversion devices will never be able to achieve high conversion efficiencies.

    This first prototype can only convert 2% heat energy to electricity, and, Professor Vassallo predicted, will have a Carnot limit of “less than 10%”.

    “While this will no doubt be improved, there are thermodynamic limits which basically say the maximum efficiency will always be low at the sort of temperatures these electrochemical cells could work at,” he said.

    When dealing with such low conversion efficiencies (generating watts rather than kilowatts), Damon Honnery – a research engineer at Monash University – said that “overcoming system losses can be a significant technical barrier”.

    But it’s not all bad, according to Associate Professor Honnery: “There is a demand for low power sources. Lots of electrical systems require low power, and there could be niche uses for smaller devices where the energy density doesn’t need to be so high.”

    On the road to application

    The researchers want to try use the technology to harvest heat from the environment in remote areas. But as solar arrays already dominate the market, and operate more efficiently, it is unlikely heat conversion technology will supercede them any time soon.

    And as the heat conversion battery needs two temperatures to operate, the battery would require fairly extreme fluctuations in temperature in order to function outside the laboratory.

    While this would be easy over long 24-hour cycles, rapid discharging is unlikely, so the amount of electricity generated over a day would be small.

    Adam Best, a senior research scientist at CSIRO, said: “like all things in batteries, it’s a materials science challenge. Can you get better materials which are able to convert this heat in a more efficient fashion?”

    Dr Best suggested the technology may be better used in industrial facilities or in tandem with other energy systems to further enhance energy production.

    See the full article here.

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    About Phys.org in 100 Words

    Phys.org™ (formerly Physorg.com) is a leading web-based science, research and technology news service which covers a full range of topics. These include physics, earth science, medicine, nanotechnology, electronics, space, biology, chemistry, computer sciences, engineering, mathematics and other sciences and technologies. Launched in 2004, Phys.org’s readership has grown steadily to include 1.75 million scientists, researchers, and engineers every month. Phys.org publishes approximately 100 quality articles every day, offering some of the most comprehensive coverage of sci-tech developments world-wide. Quancast 2009 includes Phys.org in its list of the Global Top 2,000 Websites. Phys.org community members enjoy access to many personalized features such as social networking, a personal home page set-up, RSS/XML feeds, article comments and ranking, the ability to save favorite articles, a daily newsletter, and other options.

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  • richardmitnick 3:02 pm on September 11, 2014 Permalink | Reply
    Tags: , Electricity,   

    From M.I.T.: “Physicists find a new way to push electrons around” 


    MIT News

    September 11, 2014
    David L. Chandler | MIT News Office

    When moving through a conductive material in an electric field, electrons tend to follow the path of least resistance — which runs in the direction of that field.

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    But now physicists at MIT and the University of Manchester have found an unexpectedly different behavior under very specialized conditions — one that might lead to new types of transistors and electronic circuits that could prove highly energy-efficient.

    They’ve found that when a sheet of graphene — a two-dimensional array of pure carbon — is placed atop another two-dimensional material, electrons instead move sideways, perpendicular to the electric field. This happens even without the influence of a magnetic field — the only other known way of inducing such a sideways flow.

    What’s more, two separate streams of electrons would flow in opposite directions, both crosswise to the field, canceling out each other’s electrical charge to produce a “neutral, chargeless current,” explains Leonid Levitov, an MIT professor of physics and a senior author of a paper describing these findings this week in the journal Science.

    The exact angle of this current relative to the electric field can be precisely controlled, Levitov says. He compares it to a sailboat sailing perpendicular to the wind, its angle of motion controlled by adjusting the position of the sail.

    Levitov and co-author Andre Geim at Manchester say this flow could be altered by applying a minute voltage on the gate, allowing the material to function as a transistor. Currents in these materials, being neutral, might not waste much of their energy as heat, as occurs in conventional semiconductors — potentially making the new materials a more efficient basis for computer chips.

    “It is widely believed that new, unconventional approaches to information processing are key for the future of hardware,” Levitov says. “This belief has been the driving force behind a number of important recent developments, in particular spintronics” — in which the spin of electrons, not their electric charge, carries information.

    The MIT and Manchester researchers have demonstrated a simple transistor based on the new material, Levitov says.

    “It is quite a fascinating effect, and it hits a very soft spot in our understanding of complex, so-called topological materials,” Geim says. “It is very rare to come across a phenomenon that bridges materials science, particle physics, relativity, and topology.”

    In their experiments, Levitov, Geim, and their colleagues overlaid the graphene on a layer of boron nitride — a two-dimensional material that forms a hexagonal lattice structure, as graphene does. Together, the two materials form a superlattice that behaves as a semiconductor.

    This superlattice causes electrons to acquire an unexpected twist — which Levitov describes as “a built-in vorticity” — that changes their direction of motion, much as the spin of a ball can curve its trajectory.

    Electrons in graphene behave like massless relativistic particles. The observed effect, however, has no known analog in particle physics, and extends our understanding of how the universe works, the researchers say.

    Whether or not this effect can be harnessed to reduce the energy used by computer chips remains an open question, Levitov concedes. This is an early finding, and while there is clearly an opportunity to reduce energy loss to heat locally, other parts of such a system may counterbalance those gains. “This is a fascinating question that remains to be resolved,” Levitov says.

    Francisco Guinea, a research professor at Spain’s Instituto de Ciencia de Materiales de Madrid, who was not connected with this research, calls the approach taken by this team “novel and imaginative. … The characterization of these currents in graphene is a very important advance in the understanding of two-dimensional materials.”

    The work has great potential, Guinea adds, because “two-dimensional materials with special topological properties are the basis of new technologies for the manipulation of quantum information.”

    In addition to Levitov and Geim, the research team included Roman Gorbachev, a research fellow at Manchester; Justin Song, a graduate student at MIT who is now at Caltech; Geliang Yu, a graduate student at Manchester; Freddie Withers, Yang Cao, and Artem Mishchenko, who are postdocs at Manchester; and Manchester professors Irina Grigorieva and Konstantin Novoselov. The work was supported by the European Research Council, the Royal Society, the National Science Foundation, the Office of Naval Research, and the Air Force Office of Scientific Research.

    See the full article here.

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