Protecting the Electrical Grid
Fugro Roames engineers use machine learning in Julia to identify network failures and potential failures 100x faster
ARPA-E (Advanced Research Projects Agency - Energy) is a project of the US Department of Energy using Julia for a number of projects including collaborations with Mitsubishi Electric Research Laboratories, Carnegie Mellon University, MIT, Los Alamos National Laboratory, Quantumscape and others.
Électricité de France’s Jérôme Collet uses Julia to forecast electricity demand.
Fugro Roames is a large utility using Julia machine learning tools to identify network failures and potential failures 100x faster.
AOT Energy is an energy trading firm using Julia for options pricing and market simulations in the energy sector.
PSR uses Julia for energy market simulation, analytics and planning.
LAMPS PUC-Rio uses Julia for applied energy optimization research.
Los Alamos National Laboratory uses Julia for critical infrastructure optimization.
Invenia uses Julia to optimize the North American electrical grid.
Tangent Works uses Julia for real-time energy forecasting.
Other Julia users in the energy industry include Chevron, ExxonMobil and all of the US Department of Energy National Laboratories: Ames, Argonne, Brookhaven, Fermi, Frederick, Idaho, Lawrence Berkeley, Lawrence Livermore, Los Alamos, National Energy Technology Laboratory, National Renewable Energy Laboratory, Oak Ridge, Pacific Northwest, Princeton Plasma Physics, Sandia, Savannah River, SLAC National Accelerator and Thomas Jefferson National Accelerator.
Watch our webinar to see how to improve the process with JuliaHub.
Julia provides faster, more efficient optimization using JuMP and other optimization packages.
Julia is the fastest language for machine learning, artificial intelligence, risk analysis, Monte Carlo simulations and other energy uses.
Julia is easy to learn and easy to code. Spend your time improving energy delivery and efficiency - not writing code.
Stop prototyping in one language and deployment in a second language. Julia delivers the speed of C with the ease of use of Python.
Leverage GPUs, TPUs, supercomputers and other advanced hardware easily and seamlessly with Julia.
There are more than 6,000 registered Julia packages, including the best optimization packages available in any language.
Fugro Roames engineers use machine learning in Julia to identify network failures and potential failures 100x faster
Invenia Technical Computing is scaling up its energy intelligence system using Julia
Watch our webinar “JuliaHub 101”
WEBINAR