🌊 Transforming Wastewater Management: AI-Driven Aeration Control for Energy Efficiency and ComplianceA wastewater treatment plant in Californ...
Published on by Hossein Ataei Far, Ambassador for Sustainability | Water & Energy PPP Finance Facilitator
A wastewater treatment plant in California successfully implemented AI-based aeration control within its activated sludge system.
Project Goals
1. Energy Savings
2. Nutrient Removal Compliance
3. Operational Efficiency
Implementation Steps:
1. Assessment and Baseline Evaluation
Conducted energy audits to identify over-aeration inefficiencies.
Reviewed nutrient removal performance, identifying inconsistencies in meeting nitrogen and phosphorus discharge standards.
2. Technology Deployment
Installed AI-based aeration control software integrated with existing SCADA systems for seamless real-time monitoring and adjustments.
Deployed sensors to measure critical parameters such as dissolved oxygen (DO), ammonia, and nitrate, ensuring accurate data inputs for AI.
3. Optimization and Feedback
Utilized AI to dynamically adjust DO levels across different aeration zones.
Applied predictive algorithms to anticipate influent variability and optimize aeration during peak flows.
Continuously monitored performance metrics to refine AI algorithms and improve outcomes.
Results Achieved
1. Energy Cost Savings
Achieved $200,000 in annual savings.
Reduced aeration energy consumption by 25–35% compared to baseline levels.
2. Enhanced Nutrient Removal
Consistently met nitrogen standards (