Reducing Hydraulic Capacity Flood Risk through Monitoring and Autonomous Local Control. Prof Pete Skipworth, EMS

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Muriel Arnold
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1 Reducing Hydraulic Capacity Flood Risk through Monitoring and Autonomous Local Control Prof Pete Skipworth, EMS

2 Types of Flooding Inundation flooding e.g. a river bursts its banks Hydraulic incapacity The drainage network cannot convey the event Flooding other causes (FOC) e.g. bockages

3 Traditional Approaches Build storage, enlarge sewers capital- and often space- intensive space and capital are at a premium

4 Intelligent autonomous system for local urban flood risk reduction Utilises untapped network capacity Gate controls flow based on intelligent algorithm which leverages local level data Low-cost alternative to traditional capital- and space-intensive solutions Easily deployed

5 Project Partners EMS responsible for actualising monitoring and control system

6 Concept

7 Concept Return period (years) Existing Flood Vol (m 3 ) Residual Flood Vol (m 3 ) with CENTAUR Captured flood volume % % % % % % %

8 Depth (%) Rainfall intensity (mm/hr) 5 yr return, 120 min event Flood volume 247m 3, duration 290 minutes Time (h) Flood Location Depth Depth Upstream of Flow Control Rainfall (mm/hr)

9 Depth (%) Flow control setting (1 = 100% open) 5 yr return, 120 min event, CENTAUR Flood volume 113m 3, duration 180 minutes Time (h) Flood Location Depth Depth Upstream of Flow Control Flow Control Setting

10 protected site Flooding in Coimbra, Portugal flow control site Flow Direction

11 Fuzzy Logic algorithm

12 OPERATIONAL VISIBILITY Level and status in real-time On screen alarming SCADA integration REMOTE RECONFIG Dashboard connected to Hub Pass-through to other units online DASHBOARD

13 Control Algorithm Levels relayed to Control Hub Control Hub uses Fuzzy Logic to decide gate actions Spare capacity optimised to attenuate effects at target site

14 Fail Safes Triple redundancy in level measurement Comms failure: system can disable itself and fully open Physical failures: complete overflow of gate

Modelling Real-time response simulated by University of Sheffield 120 100 1.2 1 Using SWMM 80 60 0.8 0.

15 Depth (%) Flow control setting (1 = 100% open) Modelling Site Selection Specialist modelling tool from EAWAG Freeware Import asset data Identifies sites with greatest potential to reduce risk at target site Dynamic Modelling Real-time response simulated by University of Sheffield Using SWMM Time (h) Flood Location Depth Depth Upstream of Flow Control Flow Control Setting

Deployment and Cost Enabling works All elements lamp-post mounted or in-manhole Other than kiosk at Control Site Up to 500mm dia gate can go through a 600mm manhole cover Power Cost 240VAC

16 Deployment and Cost Enabling works All elements lamp-post mounted or in-manhole Other than kiosk at Control Site Up to 500mm dia gate can go through a 600mm manhole cover Power Cost 240VAC supply for gate All other elements self-powered (solar and/or batts 5 yr target) Power-optimised economy and operational modes An order of magnitude less than equivalent traditional solution

Comms Protocols and Cyber Security Comms Protocols Local radio comms for monitoring and control (reliable and low latency) Mobile phone (3G) for comms between internet & Control Hub; configuring,

17 Comms Protocols and Cyber Security Comms Protocols Local radio comms for monitoring and control (reliable and low latency) Mobile phone (3G) for comms between internet & Control Hub; configuring, monitoring Blue-tooth for local comms Cyber security Radio comms network secure proprietary protocol Web portal based on MS Azure search Azure cyber security Control Hub to Portal JSON (SSL security for message encryption) Bluetooth opened as required

(Level to Repeater, Repeater to Hub) lab

power, reliable, triple redundancy (flagged

18 Operation Robustness and Reliability Prototyping signal, power, reliability issues all addressed in beta version prototyping Comms protocols optimised (Level to Repeater, Repeater to Hub) lab Low Maintenance Pressure transducers: low power, reliable, triple redundancy (flagged when compromised) Wet-well installation in benching to avoid ragging field

19 The Journey

20 Other Uses Different uses for CENTAUR Flood protection Limiting CSO spills Regulating flows into energy intensive assets Complementary solution, e.g. reduce size of an intended storage tank, combine with SUDS Clustered to form IWANs (Intelligent Wastewater Networks) Multi-objective (and at multiple points in a DA) capacity and flooding, environmental impact, energy Full and Automated Drainage Area Control and Visibility

21 System Summary Disruptive technology Easy deployment, maintenance and operation Orders of magnitude lower cost than traditional approach Space-efficient Existing technology: developed to TRL8 Successfully Deployed: in Coimbra, going into Toulouse (Veolia) It could be said that the increased network handling capacity and financial benefits (capital avoided) come from the Fuzzy Logic algorithm. However, without the robustness, reliability and advances in monitoring and comms technologies as the enablers, the effective application of AI would not be possible.

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