The Power of Prediction: Using Pumped Storage Hydropower to Ensure Electric Grid Stability

Renewable energy sources play a critical role in reducing greenhouse gas emissions and ensuring a sustainable future for our planet. However, as the electric grid increasingly shifts towards intermittent renewable power, maintaining grid stability becomes a significant challenge. To address this issue, scientists at Oak Ridge National Laboratory (ORNL) and the University of Tennessee, Knoxville (UTK), have developed an innovative algorithm that harnesses the power of pumped storage hydropower (PSH) to predict electric grid stability.

Hydropower has long been recognized as a reliable and renewable energy source that provides inertia to the grid. When water spins the large turbines of hydropower plants, it creates kinetic energy, known as inertia, which helps maintain the balance between power supply and demand on the grid. However, the rise of intermittent renewable sources like solar and wind, which lack significant inertia, poses a challenge to grid stability.

Pumped storage hydropower addresses the issue of intermittent power supply by acting as an energy storage bank. During times of low power demand, excess electricity from the grid is used to pump water from a lower to an upper reservoir. This stored energy can then be released during periods of high demand by allowing the water to flow back to the lower reservoir through the turbines, generating electricity in the process.

The research team led by Yilu Liu, the UT-ORNL Governor’s Chair for power grids, recognized the potential of pumped storage hydropower to provide a valuable signal for predicting grid stability. The pumps in PSH projects typically stop at a fixed power level, creating a distinctive signal on the grid. By capturing this signal and combining it with data from low-cost grid sensors deployed nationwide, Liu and his colleagues developed a cutting-edge algorithm.

The team utilized the FNET/GridEye system, previously developed by ORNL and UTK researchers, to gather real-time data from the grid. This system monitors the grid over a wide area and provides vital information for estimating grid inertia. By incorporating the PSH signal and the data from the grid sensors, the algorithm can offer grid operators a highly accurate estimation of grid inertia, enhancing situational awareness and better preparing for potential grid instability.

The team’s research results have led to the development of a user-friendly visualization interface for grid operators. This interface allows operators to easily monitor grid inertia using the algorithm, facilitating timely interventions to prevent potential instability. The validation of the algorithm was conducted in collaboration with utilities and power regulating authorities in the western and eastern United States, where pumped storage hydropower projects are prevalent.

As the electric grid continues to rely more heavily on renewable energy sources, the need for accurate prediction and situational awareness becomes increasingly critical. The research conducted by Liu and his team highlights the importance of inertia and demonstrates the significant contribution that pumped storage hydropower can make in maintaining grid stability. By leveraging the power of PSH and advanced algorithms, grid coordinating authorities and utilities can effectively manage the challenges posed by intermittent renewable energy sources.

Shih-Chieh Kao, the manager of the Water Power Program at ORNL, underscores the significance of this research project and its implications for the future. The demonstration of the visualization tool to key industry players, such as the North American Electric Reliability Corporation, showcases the value of incorporating pumped storage hydropower into the grid infrastructure. As we witness the integration of more intermittent renewable energy sources, PSH presents a viable solution to enhance grid stability and ensure a reliable electricity supply.

The algorithm developed by the collaboration between ORNL and UTK is revolutionizing the prediction of electric grid stability. By harnessing the power of pumped storage hydropower and combining it with data from grid sensors, the algorithm provides grid operators with vital information to proactively address grid instability issues. As the world continues to embrace renewable energy, it is clear that pumped storage hydropower has a crucial role to play in ensuring the reliability and stability of our electric grids.


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