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Optimizing the Activation of WWTP Wet-Weather Operation Using Radar-Based Flow and Volume Forecasting with the Relative Economic Value (REV) Approach
Optimizing the Activation of WWTP Wet-Weather Operation Using Radar-Based Flow and Volume Forecasting with the Relative Economic Value (REV) Approach
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Optimizing the Activation of WWTP Wet-Weather Operation Using Radar-Based Flow and Volume Forecasting with the Relative Economic Value (REV) Approach
Optimizing the Activation of WWTP Wet-Weather Operation Using Radar-Based Flow and Volume Forecasting with the Relative Economic Value (REV) Approach

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Optimizing the Activation of WWTP Wet-Weather Operation Using Radar-Based Flow and Volume Forecasting with the Relative Economic Value (REV) Approach
Optimizing the Activation of WWTP Wet-Weather Operation Using Radar-Based Flow and Volume Forecasting with the Relative Economic Value (REV) Approach
Journal Article

Optimizing the Activation of WWTP Wet-Weather Operation Using Radar-Based Flow and Volume Forecasting with the Relative Economic Value (REV) Approach

2024
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Overview
Wastewater treatment plants (WWTPs) connected to combined sewer systems must cope with high flows during wet-weather conditions, often leading to bypass and thus pollution of water bodies. Radar rainfall forecasts coupled with a rainfall-runoff model provides flow and volume forecasts that can be used for deciding when to switch from normal to wet-weather operation, which temporarily allows for higher inflow. However, forecasts are by definition uncertain and may lead to potential mismanagement, e.g., false alarms and misses. Our study focused on two years of operational data from the Damhuså sewer catchment and WWTP. We used the Relative Economic Value (REV) framework to optimize the control parameters of a baseline control strategy (thresholds on flow measurements and radar flow prognosis) and to test new control strategies based on volume instead of flow thresholds. We investigated two situations with different objective functions, considering higher negative impact from misses than false alarms and vice versa, and obtained in both cases a reduction of the rate of false alarms, higher flow thresholds and lower bypass compared to the baseline control. We also assess a new control strategy that employs thresholds of predicted accumulated volume instead of predicted flow and achieved even better results.