Trillions of gallons of water are used annually to prevent power plants from overheating. A Texas A&M research group is looking into alternative methods of cooling steam turbines.
The food-water-energy nexus dictates that there is a direct link between these three necessities, and stressing one directly impacts the supply of the other two. As the population grows, human demand for energy and food has caused freshwater reserves to slowly deplete. Power plants are one of the main culprits contributing to this issue, as they use trillions of gallons of fresh water annually to prevent overheating.
A research group led by Debjyoti Banerjee, professor in the J. Mike Walker ’66 Department of Mechanical Engineering at Texas A&M University, has shown that specific phase change materials (PCMs) can cool steam turbines used in power plants, averting fresh water usage. Simultaneously, the group used machine-learning techniques to enhance the reliability and energy storage capacity of various PCM-based cooling platforms to develop powerful “cold batteries” that dispatch on demand.
The researchers’ publication, “Leveraging Machine Learning (Artificial Neural Networks) for Enhancing Performance and Reliability of Thermal Energy Storage Platforms Utilizing Phase Change Materials,” was published in the American Society of Mechanical Engineers Journal of Energy Resources Technology.
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