Water Modelling Trends Automating model build and maintenance - PowerPoint PPT Presentation

Water Modelling Trends Automating model build and maintenance procedure Presented by Luca Serena – PM for Water Distribution 1

About Innovyze Asset Water Supply Storm, Sewer Management & Flood Artificial Operational Intelligence Analytics 2

Presenters Luca Serena Product Manager Water Distribution Products 4

In this webinar we look at • Typical model build and maintenance procedure • Manual model build and maintenance • Automate model build and maintenance • Ideal end-to-end solution • Example model integration project • Live model and work order management 5

Typical model maintenance procedure Time Dist stribut utio ion S System em 6

Typical model maintenance procedure Time Dist stribut utio ion S System em Asset set R Reg egist istry (i.e. e. G GIS, C CMMS MMS, S SAP) P) 7

Typical model maintenance procedure Time Dist stribut utio ion S System em Asset set R Reg egist istry (i.e. e. G GIS, C CMMS MMS, S SAP) P) Simula lated / d / Obse served = d = 1 Hydraul ulic ic Mode del New model build Point of model creation extract Time me 8

9

Calibration practices • Connect to Live Data • Update boundary conditions for the calibration and verification day • Update demands • Update controls • Compare simulated vs observed 10

Typical model maintenance procedure Time Dist stribut utio ion S System em Asset set R Reg egist istry (i.e. e. G GIS, C CMMS MMS, S SAP) P) Simula lated / d / Obse served = d = 1 Hydraul ulic ic Model delivery Mode del New model build Point of model creation extract Time me 11

Typical model maintenance procedure Time Dist stribut utio ion S System em Asset set R Reg egist istry (i.e. e. G GIS, C CMMS MMS, S SAP) P) Simula lated / d / Obse served = d = 1 Hydraul ulic ic Model delivery Mode del New model build New model build Point of model creation extract Time me 12

Typical model maintenance procedure Time Dist stribut utio ion S System em Asset set R Reg egist istry (i.e. e. G GIS, C CMMS MMS, S SAP) P) Simula lated / d / Obse served = d = 1 Lack of confidence in the model Hydraul ulic ic Model delivery Model build and calibration Mode del of hydraulic models are $30k-$150k CAPEX spend every 3-5 years for water utilities New model build New model build Point of model creation extract Time me 13

Automate model maintenance procedure Time Dist stribut utio ion S System em Asset set R Reg egist istry (i.e. e. G GIS, C CMMS MMS, S SAP) P) Simula lated / d / Obse served = d = 1 Continuous “automatic” model update Hydraul ulic ic Model Delivery Mode del New Model build Point of model creation extract Time me 14

Automating model maintenance with Ruby 15

Automating model maintenance with Ruby 16

Automating model maintenance with Ruby 17

Automating model maintenance with Ruby 18

Automating model maintenance with Ruby 19

20

Automate model build and maintenance Scripts Asset Registry GIS Telemetry SAP CMMS Data Science 21

Direct pathway towards live modelling Incident Management Network optimisation Mapping water quality Forensic analysis Scripts Loop Hydraulic Modelling Telemetry Demand Forecasts Update

Ideal end-to-end solution • Example model integration project • Live model and work order management 23

Example model integration project: Benefits at a glance 1 version of the Truth Process Controller Tool Data changes updated in their Holds default parameters respective source only and aids error investigation Asset Level Tolerances Models refreshed daily With bulk changes to aid Verified against previous build adjustments and against SCADA data Auto-Publish Model Merge If verification is passed Not needed – simply update the “owning model” field of your asset (in bulk) in the GIS Modeling: from isolated discipline to part of a holist istic s strateg egy supporting water utilities in dealing with the complexity of the real-word system 24

Example model integration project Data Transfer Scripts Asset Registry GIS Telemetry SAP CMMS Data Science Process Controller Data Integration Hub

Incident Management Understand current Evidence led and future impacts decision making on service levels Incident Management Network optimisation Mapping water quality Analyse the “what- Forensic analysis Generate Work- if” scenario to Order to field crews minimise disruption Post-incident Alerts affected analysis/reporting facilities 27

Live model and Work Order Management Network Optimisation Warnings Loop Supervisory Controls Incident Management Hydrau aulic Wo Work O k Order er Telemetry Si Simulation Mana nagem ement nt Update Base se Ru Run Model Maintenance Demand Forecasts 28

Thank you Luca Serena Product Manager Water Distribution Products Luca.serena@Innovyze.com 30