Real-time Data-driven Modelling and Predictive Control of Wastewater Networks

Krisztian Mark Balla

doi:10.54337/aau495535332

Real-time Data-driven Modelling and Predictive Control of Wastewater Networks

Krisztian Mark Balla

Research output: PhD thesis

85 Downloads (Pure)

Original language	English
Supervisors	Bendtsen, Jan Dimon, Principal supervisor Kallesøe, Carsten Skovmose, Co-supervisor Schou, Christian, Company supervisor, External person
External collaborators	Grundfos DK AS
Publisher	Aalborg Universitetsforlag
Electronic ISBNs	978-87-7573-876-2
DOIs	https://doi.org/10.54337/aau495535332
Publication status	Published - 2022

Bibliographical note

PhD supervisors:
Associate Professor Jan Dimon Bendtsen, Aalborg University
Professor Carsten Skovmose Kallesøe, Aalborg University and Grundfos Holding A/S
Lead Business Dev. Manager Christian Schou, Grundfos Holding A/S

Keywords

Grundfos
Water
network
wastewater
drainage
predictive control
uncertainty
gaussian process
partial differential equation
saint venant
collection system
rain
rain forecast
flow
open channel
sewer network
pump
pumping station
grey-box
system identification
easy-commissioning
data-driven
flooding
overflow
treatment plan
learning
real time control

Access to Document

10.54337/aau495535332

PHD_KMBallaFinal published version, 39.8 MB

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Cite this

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title = "Real-time Data-driven Modelling and Predictive Control of Wastewater Networks",

keywords = "Grundfos, Water, network, wastewater, drainage, predictive control, uncertainty, gaussian process, partial differential equation, saint venant, collection system, rain, rain forecast, flow, open channel, sewer network, pump, pumping station, grey-box, system identification, easy-commissioning, data-driven, flooding, overflow, treatment plan, learning, real time control",

author = "Balla, {Krisztian Mark}",

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KW - overflow

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