Grid Modernization

DOE offers funding tied to big data, AI, machine learning

The Department of Energy has issued a $5.8 million funding opportunity for research and development of “advanced tools and controls” to improve the resilience and reliability of the nation’s power grid.

The Transmission Reliability Program part of DOE’s Office of Electricity is looking for applications that use big data, artificial intelligence, and machine learning technology and other tools to derive more value from the sensor data already being gathered and used to monitor the health of the grid and support system operations.

The DOE is seeking to fund projects that would “shape future development and application of faster grid analytics and modeling; better grid asset management; and sub-second automatic control actions that will help system operators avoid grid outages, improve operations, and reduce costs.”

Devices known as phasor measurement units measure the amplitude and phase of electric current and voltage at various points on the electric grid using a common time source for synchronization. The so-called PMUs can gather data at a rate 100 times faster than the Supervisory Control and Data Acquisition (SCADA) systems that are widely used in the power industry.

The resulting synchrophasor data provides system operators with a near real-time snapshot of the grid’s operating status that can be used to improve grid reliability and efficiency and lower operating costs.

The American Recovery and Reinvestment Act of 2009 supported the installation of over 1,000 PMUs across North America. There are now PMUs deployed at over 2,500 locations across the nation’s bulk power system.

The PMU data gives grid owners and operators vast quantities of data on the condition of the grid, but more advanced tools are needed to analyze the data for actionable information.

Additional information about the funding opportunity is available here.

NYPA Phasor Measurement Unit program

The New York Power Authority in July unveiled a Phasor Measurement Unit program, which deploys sensors to collect voltage and current data at NYPA’s power generating facilities and switchyards with high‑resolution and precise time stamping. The collected data can then be pulled together and used for real‑time grid management, asset management and potential problem detection.

Through this program, which is scheduled to be completed in 2022, NYPA is expanding the PMU installation across all of its sites and is replacing earlier models with the latest, cutting‑edge PMU technology, it said.

Also this past summer, NYPA said that it was testing an array of sensors at its Robert Moses-Niagara Power Plant that will help determine the life expectancy of key equipment and head off potential problems before they can affect operations.

NYPA said that data from about 100 sensors is currently being used in a simulation on a turbine-generator unit at the plant. However, NYPA engineers will soon seek to deploy them elsewhere as part of a larger equipment life extension and modernization program at the facility.