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UA Smart Grid Research Gets National Coverage

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UA Smart Grid Research Gets National Coverage

April 25, 2012
UA Smart Grid Research Gets National Coverage

A leading industry publication features computer models designed by UA researchers to boost "smart grid" performance.

New methods of increasing the delivery efficiency of electricity at the grid level proposed by UA researchers have been publicized by a national newsletter that reports the latest developments in "smart grid" technologies.
Grid systems that manage the supply of electricity delivered to individual households based on need aren't exactly brand new. Modern solar energy generating systems now interact directly with electrical grids to control the flow of electricity to the household, based on how much sun is hitting the panels.
But how do you manage electricity supply and demand to hundreds or thousands of homes in an electrical grid, taking into account not only how much electricity the house is using, but how much is being supplemented, what different kinds of appliances are being used, and when the household's peak usage is?
Systems that can keep track of these variables to better manage energy flows are called "smart grid" systems. One of the leading publications supporting the development of smart grid technologies is the Smart Grid Newsletter from the Institute of Electrical and Electronics Engineers, or IEEE. And this month, computer models developed by UA engineers are featured by the publication.
University of Arizona researchers (from left) Janet Roveda, Susan Lysecky and Young-Jun Son.
"A New Way to Look at Energy and Data Flows," by UA researchers Janet Roveda, Susan Lysecky and Young-Jun Son, describes new computing methods for monitoring and managing the massive amounts of information that flow into typical smart grid systems. A smart grid is a digitally enabled electrical grid that gathers, distributes, and acts on information about the behavior of multiple participants, or, namely, all of the consumers and suppliers that are tied to the grid. Smart grid systems are designed to improve efficiency and reliability of electricity delivery.
For a smart grid system to function correctly, it requires almost seamless cooperation between the software and hardware components. Some researchers consider smart grids "cyber-physical" systems, because the integration of the software (the programs telling the systems what to do, and when) and the hardware (including household appliances of assorted standards and sizes) must be nearly flawless in order for the system to control energy flows the most efficient way possible.
Data is a big problem in smart grid research, said Janet Roveda, associate professor at the UA department of electrical and computer engineering, and co-author of the report.
A new generation of smart meters can record electricity usage every minute on every appliance. Smart meters can now directly upload all these real-time data to central servers, or clouds. These data hold a lot of critical information: typical usage patterns, performance of individual appliances, and load-and-demand balancing, Roveda said. "I think if we understand the data, we can understand how to smartly manage the grid," she said. The same situation exists with solar and wind farms, which rely on continuous, real-time monitoring and data collection for smart usage. "The fundamental question really is how to harness these performance data so we can optimize the grid to deliver the best, most efficient electricity delivery," she said.
The article appears in the April 2012 issue of the IEEE Smart Grid Newsletter. Roveda's co-authors are Susan Lysecky, assistant professor of electrical and computer engineering at the UA and Young-Jun Son, professor in the UA department of systems and industrial engineering. The research was funded in part by AzRISE, the Arizona Research Institute for Solar Energy.
The April issue of the IEEE Smart Grid Newsletter can be found here
More information on the University of Arizona department of electrical and computer engineering can be found at