Pumped Storage Hydro

Researchers develop method to monitor grid stability with hydropower project signals

Researchers develop method to monitor grid stability with hydropower project signals
(Illustration of an electrical transmission line connecting a hydropower plant to industrial customers. This image was created with the assistance of DALL·E 2, an A.I. image generator)

Scientists at Oak Ridge National Laboratory and the University of Tennessee, Knoxville, have developed an algorithm to predict electric grid stability that uses signals from pumped storage hydropower projects. The method provides critical situational awareness as the grid increasingly shifts to intermittent renewable power, according to ORNL.

The method rests on calculating overall inertia. Inertia is the kinetic energy provided by the spinning parts of large power plants that maintain the grid’s balance between the push of power supply and the pull of power demand. Generation sources such as solar and wind provide a minimal amount of inertia because they are connected to the grid using inverters that convert the direct current power generated by renewables to the alternating current power used to transmit electricity over long distances.

The result is that grids reliant on inverter-connected renewable energy have less tolerance to abrupt change, such as storm damage or unusual demand peaks.

Hydropower is directly connected to the grid, providing inertia as water spins the turbines. Pumped storage hydropower (PSH) draws electricity from the grid in times of low power demand to pump water from a lower to an upper reservoir and create an energy storage bank. In times of high demand, electricity is generated by turbines as water flows back to the lower reservoir.

When the pumps shut down, they almost always stop at a fixed power level, said Yilu Liu, lead for the project and UT-ORNL Governor’s Chair for power grids. “That’s a very defined signal on the grid that can help us calculate overall inertia,” Liu said.

Liu and colleagues created an algorithm that captures the PSH signal and uses it, along with information gathered from low-cost grid sensors previously deployed across the U.S. That sensing and measurement system, FNET/GridEye, was developed by ORNL and UTK researchers to monitor the grid across a wide area. Together, the PSH signal and sensor data produce a real-time, highly accurate estimation of grid inertia.

The researchers created a visualization interface that makes it easy for grid operators to monitor inertia using the algorithm and better prepare for potential grid instability. The new method was validated with the help of utilities and power regulating authorities in the western and eastern U.S., where pumped storage hydropower is most prevalent.

“What we’re providing will become more and more important for grid situational awareness as the system grows increasingly reliant on renewables,” Liu said. The visualization tool is being demonstrated to utilities and grid coordinating authorities such as the North American Electric Reliability Corporation.

The project was supported by the Water Power Technologies Office of the Department of Energy’s Office of Energy Efficiency and Renewable Energy as part of the HydroWIRES initiative to leverage hydropower for greater grid reliability and resilience. FNET/GridEye was developed with support from DOE’s Office of Electricity.

UT-Battelle manages ORNL for the Department of Energy’s Office of Science.