Nonlinear Grey-Box Identification with Inflow Decoupling in Gravity Sewers

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

Knowing where wastewater is flowing in drainage networks is essential to utilize system storage, predict overflows and to optimize system operation. Unfortunately, flow in gravity-driven sewers is subject to transport delays, and typically influenced by significant disturbances entering the sewer pipes in the form of domestic, ground and rain inflows. Model-based optimal control of urban drainage requires knowledge about these inflows, even though it is often not feasible in operational setups. To this end, we propose a lumped-parameter hydrodynamic model with a bi-linear structure for identifying the transport delays, decouple periodic disturbances and to predict the discharged flow. Pumped inlet and discharged dry- weather flow is used to find the model parameters. Under mild assumptions on the domestic and groundwater inflows, i.e. disturbances, the decoupling capabilities of the identified model are presented. A numerical case study on an EPA Storm Water Management Model (EPA SWMM) and experimental results on a real network demonstrate the proposed method.
Original languageEnglish
Title of host publicationNonlinear Grey-Box Identification with Inflow Decoupling in Gravity Sewers
Number of pages6
PublisherIFAC Publisher
Publication statusAccepted/In press - 27 Feb 2020

Keywords

  • Process Identification
  • Transport delays
  • Disturbance parameters
  • Open hydraulics
  • Grey-box Identication
  • Sewer Networks
  • Time Delays
  • System Identification
  • Fourier series

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  • Cite this

    Balla, K. M., Kallesøe, C., Schou, C., & Bendtsen, J. D. (Accepted/In press). Nonlinear Grey-Box Identification with Inflow Decoupling in Gravity Sewers. In Nonlinear Grey-Box Identification with Inflow Decoupling in Gravity Sewers IFAC Publisher.