As part of a collaborated research project by Fraunhofer Institute for Open Comminication Systems FOKUS, Engineering Company Prof. Dr. Sieker mbH, Chair of Distributed and Operating Systems, TU Berlin and Chair of Fluid System Dynamics, TU Berlin an „Intelligent Pumping Station“ is being developed. In the project, the operation of wastewater pumping stations is optimized in two ways: by integrating precipitation forecasts and recording the operating condition,&nbsp; and by integrating historical data on use and operation. The individual strategies for optimizing the pumping stations&nbsp; and the possibilities of data integration will be systematically investigated.Data integration will enable predictive load management in the sewer system. Load forecasts determined from historical data and simulations can be used to generate an inflow forecast for the pumping station. This opens up new possibilities:- The available storage potentials in the system can be used by early detection of heavy rain events. In this way, harmful backwater events in the sewer system as well as combined sewer overflows and stormwater overflows can be reduced.- Anticipatory operation of wastewater pumping stations can provide energy savings over regular operation. A quantitative potential analysis of these savings and the hydraulic effects of predictive load management will be investigated in this project.The focus of this paper is on the method for developing the optimized pump control. It examines how knowledge of the predicted inflow can be used to achieve energy savings and a reduction in wastewater overflows. The method is based on the development of an algorithm in which detailed pump specifics and future pumping station inflow can be used to predict all possible suction head level curves for a considered period of time. Depending on the target criterion - minimum energy consumption per transported cubic meter or minimum overflow volume - the algorithm calculates the optimum path from all possible suction chamber level curves.In the energy-optimized case, this is not, as might be expected, near the respective operating points of best efficiency, but runs along the path in which the static suction-side pressure can be utilized in the best possible way.There are a number of boundary conditions that should be observed in the regular operation of pumping stations. These include mininmum/maximum pipe flow velocity, minimum/maximum rotational speed and, for safety reasons, a maximum suction chamber level. In exceptional cases these conditions can be disregarded for a limited time. In the event of a predicted heavy rainfall with corresponding overloading of the pumping station, the algorithm automatically overrides these boundary conditions and selects from the suction chamber level curves the one in which a minimum overflow is generated.The predictive load management, consisting of inflow forecasting and optimizing control algorithm, can be applied to any wastewater network structure.

Control Optimization Through Prediction-Based Wastewater Management

Paper Proceedings: https://asmedigitalcollection.asme.org/FEDSM/FEDSM2021/volume/85284

ASME 2021 Fluids Engineering Division Summer Meeting (FEDSM2021)

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