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RESEARCH PRODUCT

A data-driven methodology to support pump performance analysis and energy efficiency optimization in Waste Water Treatment Plants

Ulrich LeopoldGeorges SchutzJoachim HansenFrancesc Hernández-sanchoDario TorregrossaAlex Cornelissen

subject

EngineeringWaste managementbusiness.industryEnergy management020209 energyMechanical EngineeringComputerApplications_COMPUTERSINOTHERSYSTEMS02 engineering and technologyBuilding and ConstructionEnergy consumption010501 environmental sciencesManagement Monitoring Policy and Law01 natural sciencesData-drivenSystem dynamicsEnergy conservationWaste treatmentGeneral Energy0202 electrical engineering electronic engineering information engineeringbusinessProcess engineeringEnergy (signal processing)0105 earth and related environmental sciencesEfficient energy use

description

Abstract Studies and publications from the past ten years demonstrate that generally the energy efficiency of Waste Water Treatment Plants (WWTPs) is unsatisfactory. In this domain, efficient pump energy management can generate economic and environmental benefits. Although the availability of on-line sensors can provide high-frequency information about pump systems, at best, energy assessment is carried out a few times a year using aggregated data. Consequently, pump inefficiencies are normally detected late and the comprehension of pump system dynamics is often not satisfactory. In this paper, a data-driven methodology to support the daily energy decision-making is presented. This innovative approach, based on fuzzy logic, supports plant managers with detailed information about pump performance, and provides case-based suggestions to reduce the pump system energy consumption and extend pump life spans. A case study, performed on a WWTP in Germany, shows that it is possible to identify energy inefficiencies and case-based solutions to reduce the pump energy consumption by 18.5%.

https://doi.org/10.1016/j.apenergy.2017.09.012