RFP for the Development of Innovative Predictive Control Strategies for Nutrient Removal

The Water Research Foundation (WRF) has issued an RFP for the development of innovative predictive control strategies for nutrient removal.

According to the foundation, the implementation of online monitoring and automated control strategies is an integral part of achieving process efficiency and the intensification at water resource recovery facilities (WRRFs). Many control strategies currently in place at WRRFs are based on reactive approaches that require large design safety factors to ensure reliability in the absence of more advanced, precise controls. Implementation of modern data-driven, predictive control tools has shown promise to improve reliability of operations, with better overall process performance, and with an immediate return on investment (ROI). 

This project will focus on innovative predictive control tools for nutrient removal and provide guidance related to applications and comparison to more reactive control strategies including: demonstration of novel predictive control concepts in pilot/full-scale systems; comparison of predictive and reactive control strategies based on application, benefits, and drivers; assessment of the impacts of control strategies on the ability to achieve efficient and reliable reduction of nutrients in the effluent; evaluation of the feasibility of using process modeling in advanced process control; identification of a few specific control strategies that could be implemented based on effluent requirements; and description of gaps and considerations that would need to be identified as the tool is used/refined in the future (e.g., long-term reliability, accuracy, and dependency).

This project is open to creative deliverable products, such as a final report or guidance document on predictive tool implementation along with the modeling approach and a demonstration or recording of the model and machine learning (ML) tool being practically applied at a utility. Project objectives include development of one or more artificial intelligence /machine learning predictive tools for nutrient removal; and demonstrated testing of new predictive control strategies, with a focus on Technology Development Level 2 or 3 (Technology Readiness Level 6-8), with field testing at one utility. This field testing will be complemented by desktop analysis comparing predictive and reactive control strategies. Applicants may request up to $200,000.

Proposals will be accepted from domestic or international entities, including educational institutions, research organizations, governmental agencies, and consultants or other for-profit entities.

For complete program guidelines and application instructions, see the Water Research Foundation website.