Energy saving in WWTP: Daily benchmarking under uncertainty and data availability limitations.

Area of Science:

• Environmental Engineering
• Water Treatment Technologies
• Industrial Process Optimization

Background:

• Efficient management of Waste Water Treatment Plants (WWTPs) offers significant environmental and economic advantages.
• Energy benchmarking is a valuable tool for comparing WWTP performance and identifying improvement targets.
• Traditional benchmarking methods suffer from time lags due to infrequent data collection, hindering timely management responses.

Purpose of the Study:

• To propose a methodology for daily energy benchmarking in WWTPs despite database limitations.
• To address the challenge of infrequent water quality parameter measurements in energy Key Performance Indicator (KPI) calculations.
• To enable faster and more effective performance evaluation and management of WWTPs.

Main Methods:

• Development of a methodology for daily benchmark analysis under limited data availability.
• Application of the methodology within the Energy Online System (EOS) framework.
• Estimation of unavailable water quality parameters and management of associated uncertainty.
• Coupling parameter estimation with an interval-based benchmark approach.

Main Results:

• A methodology enabling daily energy benchmarking for WWTPs was developed and applied.
• The approach effectively manages infrequent inlet measurements by estimating required parameters.
• Uncertainty in parameter estimation was managed, allowing for reliable KPI calculations.
• The system facilitates comparison of WWTP performances across different loads and conditions.

Conclusions:

• The proposed methodology provides an effective, fast, and reproducible way to manage infrequent measurements for daily benchmarking.
• This approach significantly reduces the management response time in WWTP operations.
• It lays the groundwork for further investigations into optimizing energy performance in urban water cycles.