As energy costs continue to increase, water and wastewater agencies throughout the state are exploring strategies to lower energy expenses while adhering to stricter effluent discharge regulations. A feature presentation at CWEA’s AC25 will spotlight a pilot project by Silicon Valley Clean Water (SVCW). The presentation will demonstrate how integrating an AI power programming advisor into SVCW’s biogas microgrid can help recommend optimal setpoints for the cogenerator.
“Wastewater biogas is a renewable energy resource that can be deployed with other on-site energy resources as a biogas microgrid that reduces electricity bills and earns revenues from offering demand response to the grid,” said Jose Bolorinos, CEO of FLOWS Energy, who is co-presenting at AC25 with SVCW’s senior engineer Alex Miot. “In contrast to a typical biogas generation system that combusts biogas as it leaves the digester, a biogas microgrid controls the timing of a facility’s net electricity demand to maximize financial value.”
Bolorinos clarifies that this control results from precise forecasting of baseload electricity demand combined with real-time predictive management of various energy storage types, such as batteries, gas holders, and food waste storage.
SVCW’s pilot program features an AI-driven biogas microgrid advisor designed to suggest optimal setpoints for a 1.26 MW cogenerator and a 2 MWh/1 MW Tesla Powerpack for the operations team. The system operates on a SCADA data stream, transmitting information every five minutes. Neural networks project facility demand and biogas production from one to 24 hours ahead. A machine learning algorithm utilizes these predictions to determine the best setpoints for battery charging and discharging, and for blending natural gas into the cogeneration engines.
“FLOWS Energy is a startup spun out of Stanford in 2024. It is the culmination of a Stanford DOE-funded research project that was conducted in collaboration with SVCW,” Bolorinos said. “The project started in the summer of 2020 and has involved data sharing from SVCW and regular meetings and feedback.”
SVCW deployed its cogeneration engines in 2014 and its battery in 2020. The energy advisor featured in the presentation is a virtual pilot that is intended to be fully implemented at SVCW in 2025.
The AI programming is Stanford-funded and manages all of the applied research that is being spun out of FLOWS Energy. The research was originally Bolorinos’s PhD project through Stanford’s Sustainable Systems Lab in the Department of Civil and Environmental Engineering and was conducted in collaboration with Water and Energy Efficiency for the Environment Lab in the same department.
Based on his research, Bolorinos believes that the AI programming advisor’s help will simulate bill savings and demand response revenues equivalent to roughly $300,000 per year, or 33% of SVCW’s baseline electricity costs. SVCW’s battery could pay for itself in less than eight years, earning more than 40% over its 15-year lifetime.
“These results highlight the potential for using electric time-of-use energy and demand charges to reduce electricity costs for wastewater facilities across California, both with biogas microgrids and other energy flexibility resources,” Bolorinos said.
The presentation will include a demonstration of the user interface used by SVCW operators to interact with the energy advisor, view battery and natural gas blending set points, and browse electricity bill savings estimated relative to baseline operation.
Join this session at the Annual Conference in Palm Springs on Friday, April 25 at 11:10 p.m. Details here.
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