Predictive Control Platform for Wastewater Treatment Energy Storage and Generation

Stanford researchers in the WE3 and S3 Labs developed a cloud-based computation and predictive control platform for wastewater treatment facilities energy storage and energy generation. Wastewater treatment is energy and cost intensive. Electricity demand charges often account for a large share of electricity costs, creating strong incentives for shifting load peaks away from time-of-use periods. INtegrated FLexible Operation of Wastewater Systems (ENERGY-INFLOWS) is a computational platform for integrated management of the energy flexibility upgrades available to wastewater treatment facilities including: biogas storage, water storage, and batteries. The tool uses facility-specific metering data and treatment characteristics to identify cost-optimal energy flexibility upgrades. Its runtime controller uses artificial intelligence and facility-specific load models to operationalize a facility's existing energy flexibility resources in real-time. Overall, the tool provides a scalable platform for facilities to lower electricity costs and earn revenues from the sale of demand response and other services to electricity grids.

Stage of Development – Prototype