Project #5121

Development of Innovative Predictive Control Strategies for Nutrient Removal

$675,524
In Progress
Principal Investigator
Bruce
Johnson
Research Manager
Ms. Stephanie Fevig, PE
Contractor
Jacobs
Intelligent Water Systems
Nutrients
Big Data
Biological Nutrient Removal (BNR)
Sensors

Abstract

Water resource recovery facilities (WRRFs) are under pressure to improve effluent quality and reduce capital and operational costs. One emerging cost-saving strategy is the use of advanced process control concepts for nutrient management that combine online measurements and real-time process control. This project aims to develop and test a hybrid (machine learning + mechanistic model) nutrient management controller at three different WRRFs. The controller will demonstrate both short-term optimization functions and long-term predictive capabilities. The design of the controller, its performance at the WRRFs, and a description of future improvements will be documented. Research partner: Alexandria Renew Enterprises.

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