Energy (Oil, Gas & New Energies)
Name
Cloud-based Machine Learning to Increase Heterogenous Feedstock Conversion to Renewable Natural Gas
Description
The widespread treatment of organic carbon as a waste instead of an anaerobic digestion feedstock for renewable natural gas [RNG] is a problem. The solution requires advancements in real-time characterization of heterogeneous feedstocks to ensure digester operation remains stable while also maximizing RNG production. With AVEVA, our team partnered with municipal, on farm, and industrial facilities to use CONNECT, Communities, and Advanced Analytics to bring real-time feedstock composition predictions to operators.
Speakers