David Konstantin Tilcher, F. Popescu, H. Sommer, L. Thamsen, P. Thamsen
{"title":"Control Optimization Through Prediction-Based Wastewater Management","authors":"David Konstantin Tilcher, F. Popescu, H. Sommer, L. Thamsen, P. Thamsen","doi":"10.1115/fedsm2021-65375","DOIUrl":null,"url":null,"abstract":"\n As part of a collaborative research project (OPTIMA) by Fraunhofer FOKUS, Engineering Company Prof. Dr. Sieker mbH, Department of Distributed and Operating Systems and Department of Fluid System Dynamics, TU Berlin, an „Intelligent Pumping Station” is being developed. In this research project, the operation of wastewater pumping stations is to be optimized by integrating precipitation forecasts and recording operating conditions on one hand, and by integrating historical data on use and operation on the other. The individual strategies for optimizing the operation of pumping stations and the possibilities of data integration will be systematically investigated.\n The focus of this paper is on the method for developing an optimized pump control. It examines how knowledge of predicted inflow can be used to achieve energy savings and a reduction in wastewater overflows. This method is based on the development of an algorithm in which detailed consideration of pump specifics and future pumping station inflow can be used to predict all possible suction head level curves for the 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.","PeriodicalId":23636,"journal":{"name":"Volume 2: Fluid Applications and Systems; Fluid Measurement and Instrumentation","volume":"58 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 2: Fluid Applications and Systems; Fluid Measurement and Instrumentation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/fedsm2021-65375","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
As part of a collaborative research project (OPTIMA) by Fraunhofer FOKUS, Engineering Company Prof. Dr. Sieker mbH, Department of Distributed and Operating Systems and Department of Fluid System Dynamics, TU Berlin, an „Intelligent Pumping Station” is being developed. In this research project, the operation of wastewater pumping stations is to be optimized by integrating precipitation forecasts and recording operating conditions on one hand, and by integrating historical data on use and operation on the other. The individual strategies for optimizing the operation of pumping stations and the possibilities of data integration will be systematically investigated.
The focus of this paper is on the method for developing an optimized pump control. It examines how knowledge of predicted inflow can be used to achieve energy savings and a reduction in wastewater overflows. This method is based on the development of an algorithm in which detailed consideration of pump specifics and future pumping station inflow can be used to predict all possible suction head level curves for the 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.