New method monitors grid stability with hydropower project signals

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Scientists at Oak Ridge National Laboratory and the University of Tennessee, Knoxville have developed an algorithm to predict electrical grid stability using signals from pumped storage hydroelectric projects. This method provides critical situational awareness as the grid rapidly shifts to intermittent renewable energy.

ORNL and UT researchers created a new method to calculate power grid inertia in real time, using signals from pumped storage hydroelectric facilities like TVA's Raccoon Mountain Project, as illustrated here.

ORNL and UT researchers created a new method to calculate power grid inertia in real time, using signals from pumped storage hydroelectric facilities like TVA’s Raccoon Mountain Project, as illustrated here. Credit: Tennessee Valley Authority

Hydropower is a renewable energy source connected directly to the grid, which provides inertia when rotating large water turbines. Pumped storage hydropower, or PSH, draws electricity from the grid to pump water from a lower reservoir to an upper reservoir during times of low electricity demand to create an energy storage bank. In times of high demand, the projects generate electricity as water is pumped back into the lower reservoir through turbines.

When the pumps are turned off, they almost always stop at a certain power level, said Yilu Liu, project leader and chair of the UT-ORNL Governor’s Office for the Power Grid. “This is a very defined signal on the grid that can help us calculate the overall inertia,” Liu said.

Inertia is the kinetic energy provided by the rotating parts of large power plants that maintains the grid’s balance between the push of power supply and the pull of power demand. Generation sources such as solar and wind currently provide the minimum amount of inertia because they are connected to the grid using inverters that convert direct current electricity generated by renewable energy into alternating current power used to transmit power over long distances. Let’s convert it into.

The result is that grids relying on inverter-connected renewables have less tolerance for sudden changes such as storm damage or unusual demand peaks.

Liu and colleagues created a new algorithm that captures the PSH signal and uses it with information collected from unique, low-cost grid sensors already deployed across the country. That sensing and measurement system, FNET/GridEye, was developed by ORNL and UTK researchers to monitor the grid over a wide area. Together, the PSH signal and sensor data produce real-time, highly accurate estimates of grid inertia.

The researchers created a visualization interface that makes it easier for grid operators to use algorithms to monitor inertia and better prepare for potential grid instability. The new method was validated with the help of utilities and electricity regulatory authorities in the western and eastern United States, where pumped storage hydropower is most prevalent.

“What we are providing will become more important for grid situational awareness as the system becomes increasingly dependent on renewable energy,” Liu said. The visualization tool is being demonstrated to utilities and grid coordination authorities such as North American Electric Reliability Corporation.

“Through this project we can demonstrate how important inertia is, and how pumped storage hydro can contribute to this, especially as we are adding more intermittent renewable energy sources to the grid,” Shih-Chieh. Kao, said the manager. Jal Shakti Program At ORNL.

The project was supported by the Hydropower Technology Office of the Department of Energy’s Office of Energy Efficiency and Renewable Energy as part of the WPTO. Hydrowires Initiative Leveraging hydropower for greater grid reliability and resiliency. FNET/GridEye Was developed in collaboration with DOE’s Office of Power.

UT-Battelle manages ORNL for the Department of Energy’s Office of Science, the largest supporter of basic research in the physical sciences in the United States. The Science Office is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science,

Source: Oak Ridge National Laboratory


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