Paper: The value of CO2-Bulk energy storage with wind in transmission-constrained electric power systems
Authors: Jonathan D. Ogland-Hand, Jeffrey M. Bielicki, Benjamin M. Adams, Ebony S. Nelson, Thomas A. Buscheck, Martin O. Saar, Ramteen Sioshansi
Some storage solutions give back more than we put in
Energy is lost when batteries charge. This is the case for most energy storage solutions – we get out less than we put in. Some storage solutions, however, give back more than we put in, such as hydro-power dams. In these dams, energy is stored as elevated water (potential energy), and rivers add more water (more energy). An international team of researchers recently described an underground storage solution which could more than double the electricity put in and also help reduce CO2 in the atmosphere.
Continue reading “Doubling Electricity Production by Storing it!”
Paper: Quantifying Topological Uncertainty in Fractured Systems using Graph Theory and Machine Learning
Authors: Gowri Srinivasan, Jeffrey D. Hyman, David A. Osthus, Bryan A. Moore, Daniel O’Malley, Satish Karra, Esteban Rougier, Aric A. Hagberg, Abigail Hunter & Hari S. Viswanathan
Geophysics problems are as difficult as Nobel Prize-winning physics problems.Dr. Jérõme A.R. Noir
This quote from Dr. Jérõme Noir has stayed with me throughout my career. The idea: while physicists face extreme math, but also have extremely precise data for unknown phenomena, geoscientists must find vital solutions for known phenomena using just a few data points on a planet. With very little data, how can complex problems in geoscience be solved? And, how do we assess the risk of being wrong? An uncertainty quantification framework recently developed by researchers at Los Alamos National Lab uses machine learning to help geoscientists arrive at quality decisions using limited data.
Continue reading “A New Paradigm in Decision Making?”