Optimizing Production of Feedstock Streams from Municipal Solid Waste with Artificial Intelligence

Gasification processes are sensitive to the consistency and stability of the feedstock. GTI Energy and partners are advancing an artificial intelligence (AI) driven, real-time feed control algorithm to optimize production of feedstock streams comprised of non-recyclable municipal solids waste (NMSW).

Working with Idaho National Laboratory and West Virginia University, cutting-edge machine vision, machine learning, and advanced AI approaches are being used to implement sorting that allows for NMSW to be used as gasifier feedstock instead of going to landfills or incineration. In addition, a thermal pretreatment process (torrefaction) will be tested to improve feedstock properties. The feedstocks will be converted in a laboratory-scale gasification system based on GTI’s fluidized-bed gasifier (U-GAS) technology to generate data that will drive deployment of commercial-scale facilities.