digitalization of wastewater infrastructure as an

Technische Universität BerlinDepartment of Fluid System Dynamics

Prof. Dr.-Ing. P. U. Thamsen

Technische Universität Berlin

[email protected]

Digitalization of wastewaterinfrastructure as an opportunity to

control extrem events

mailto:[email protected]


Fluid Flow Systems & Machines

Water & Wastewater Transport

Functionality of Wastewater Pumping

Digitalization of Water & Wastewater

Fluidsystemdynamics


Extrem Events for

Water & Wastewater Systems


CHALLENGESWastewater composition

Reduced waterconsumption

Demand peaks

Cloudbursts

© wunderground.com

Droughts

© TomasCastelazo

Increasing surfacesealing

© Ralf Günther


What effects do these challenges have?

Sewer overflows Urban flooding

Low flow conditionsin sewers

Abrupt strainson the system Clogging pumps

Increased surfacerunoff


http://www.bz-berlin.de/media/gewitter-in-berlin-15

Cloudburst, June 2017, Berlin

appr. 200 mm rain within 4h !


Digitalizationin

Water & Wastewater Systems


Optimised flexible operation

Real-time control and operation

Machine 2 Machine communication

Intelligent pump control

Ressource efficiency and sustainability

Optimised data acquisition and analysis

Cyber security

Early warning systems

Digitalisation in Water and Wastewater Systems


Example 1:Pump to Pump Communication


Design of a decentralised intelligent network for 5 wet pit pumping stations

Pump to Pump Communication


11

0

20

40

00:00:00 02:24:00 04:48:00 07:12:00 09:36:00 12:00:00 14:24:00 16:48:00 19:12:00 21:36:00 00:00:00

Füllstand

0

20

40

00:00:00 02:24:00 04:48:00 07:12:00 09:36:00 12:00:00 14:24:00 16:48:00 19:12:00 21:36:00 00:00:00

FüllstandDry Weather

Rain Weather

0

0,1

0,2

0,3

0,4

0,5

0,6

0

10

20

30

40

50

60

0 50 100 150 200

Wir

kun

gsgr

ad

Förd

erh

öh

e H

in m

Volumenstrom Q in m3/h

Pumpe 1

Pumpe 2

IMEBAPumpe

Wirkungsgrad Pumpe 1

WerchauWildenau

JeßnigkDubro

Grassau

77,16 m

78,85 m

80,11 m

80,54 m 83,90 m

82,8 m

85,10 m

84,16 m81,73 m

80,59 m

76,95 m

79,70 m 82,45 m

79,88 m 83,80 m

WWTP

ZIM HerzbergPump to Pump Communication


2

3

4

5

Decentralized Operation Control

Dry / Rain Regime

Level control

Priority decision from upstreampumping station

Avoidance of overflow



Geländeoberkante

Geländeoberkante

Simulation Heavy Rain (5 m3/h, 1h) with intelligent operation control

Simulation Heavy Rain (5 m3/h, 1h)



Input parameters: Level, pressure, pump status, etc.

Automated calculation of system status

Use of numerical and hydraulic model

Numeric model: Dynamic optimization of wastewater distribution, optimal state of network (e.g. specific energy, flow,

pressure)

Hydraulic model: Review results of optimization and response of system and receive instructions for plc’s

ResearchDynamic Optimization of Wastewater Network


Example 2:Intelligent

Pumping Station


Intelligent Pumping Station (Norway)


Credits: Global Omnium

IoT SENSORS INSTALLATION

Source: Górriz Peris, 2019



Research

IoT sensor network to monitor operation of wastewater pumping stations • monitor pump operations in quasi real-time

• data-driven anomaly detection (e.g. clogging)

• predictive pump maintenance using easy to install IoT sensors



Credits: Global Omnium

REAL-TIME MONITORING

Source: Górriz Peris, 2019



Further Test Standsfor

Digitalization


• Dry & wet Pumping Station

• PCS7 Control, SIMATIC

• COMOS, SIMOCODE, Context Capture, etc.

• Digital Twin

Development of new Sensors, Actors, Algorithm, etc.

Teststands for Digitalization


Research Demo Digital Twin


Kontakt:

Prof.-Dr.-Ing. Paul Uwe Thamsen

[email protected]

Thank You for Your Attention!

mailto:[email protected]

digitalization of wastewater infrastructure as an

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