New algorithm uses smart meter data to improve power grid reliability
A new algorithm to improve power grid situational analysis drawing on residential smart meter data has been developed by Arizona State University researchers.
While currently situational awareness technology uses two software modules to measure power grid parameters, one to verify topology information and the other to determine system state, the new and more complex algorithm identifies all the necessary parameters at once along with improvements claimed in the accuracy and speed at which the parameters are determined.
Moreover, the use of homes’ individual smart meter data avoids using measurements from a limited number of devices that may not provide the full picture of a grid’s status and eliminates the need to install a large number of additional measurement devices in the distribution network.
“This technology enhances situational awareness, which is key for improving power system resilience,” says Mojdeh Khorsand Hedman, assistant professor of electrical engineering at ASU, who led the research with doctoral student Zahra Soltani.
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“The [situational awareness] functionalities are highly dependent on the availability of measurements throughout the distribution network. Such measurement devices are scarce and often not available. Thus, the [grid parameter] modules are not fully utilised.”
The motivation for the development of the algorithm was the growing presence of electric vehicles and distributed energy resources with the need for more accurate distribution network modelling and efficient management of these resources.
With the increased variability in the resultant grid conditions, greater accuracy in situational awareness is becoming necessary.
The new algorithm was developed with funded from the US Department of Energy’s Advanced Research Projects Agency – Energy (ARPA-E) and tested with an electricity utility company in Arizona.
The researchers intend that the algorithm should improve power service for customers by reducing the duration of outages and making the voltage sent to customers more stable.
With the ability to pinpoint power grid issues with greater accuracy and speed, utility workers also should be enabled to solve outages and malfunctions faster.
Currently, the technology has a provisional patent, which means the researchers have 12 months of protection on their technology until a permanent patent is filed.
ASU is also in discussions with interested industry parties to license the technology.
Meanwhile, Khorsand Hedman is in the process of developing a lab that simulates a utility company’s control room, where the new algorithm, as well as other power grid algorithmic innovations, will be demonstrated and compared to traditional solutions.
The lab is also intended to provide electrical engineering students with experience working in a simulated utility control room environment using the various types of software they would work with at a utility company.
