Improving Efficiency of Water Systems: practical examples

Transcription

1 Improving Efficiency of Water Systems: practical examples May 2012 Dr.ir. Slavco Velickov Water Industry Director EMEA

2 Agenda 1.Bentley at a Glance 2.Water Solutions Overview 3.Trends in the Water Industry 4.Practical Cases: 1.Active Leakage Management 2.Lifecycle Asset Management 3.Energy Efficiency Improvement 5.Contact Information & Resources 2

3 Bentley at a glance Revenues by Region 3

4 Solutions Bridges Power Generation Rail and Transit Buildings Communications Cadastre and Land Development Electric and Gas Utilities Campuses Factories Roads Metals and Mining Water and Wastewater Oil and Gas 4

5 The World of Water Estuaries and coastal water systems Rural water systems Urban water systems 5

6 Water Industry Solutions AutoCAD ArcGIS Industry Framework Modeling Framework sisnet WWater (Bentley WWater) Expert Designer sisnet Water (Bentley Water) SewerGEMS / CAD Hammer CivilStorm / PondPack StormCAD / HEC-Pack WaterGEMS /CAD GasAnalysis Web clients GIS products MicroStation Modelling products Web Publishing GeoSpatial Server & AssetWise Interoperability Connectors Enterprise Connectors Data Files Data Files w/ Database Linkages Spatial Databases Web Services Spatial Documents Business Documents Ancillary Files w/ RDBWS Proprietary GIS Databases Enterprise Data Stores SCADA & Loggers

7 Water & Wastewater Industry Challenges Regulatory Compliance Adequate Supply & Treatment capacity Protecting Water Quality Business performance Improving efficiency Reliability Consistently achieving target levels of services Maintaining aging infrastructure Avoiding failure Budget Reducing costs while improving services Asset investment planning for aging infrastructure Aging workforce 7

8 The Evolution of Smart Water Networks 8

9 The Smart Water Network - Integration Hydraulic Models Enterprise GIS system Online model SCADA system Planning and Demand forecasting CRM, WO Call Centre 9

10 1) Leakage Reduction Case Studies by pressure management, hydraulic modelling, measured data and optimization techniques 10

11 A Worldwide Problem: Controlling and Remediating Water Loss Is Complex It s impossible to find and fix all leaks Partial implementation of a water loss plan is highly likely to fail Coordination between all components of a water loss program is required Many practitioners make common mistakes- they may have the false impression that each time a leak is repaired, physical loss is reduced by the volume saved Vermersch and Rizzo Source: IWA s Water21 Magazine, April IWA = International Water Association (Courtesy Dr. Thomas Walski)

12 IWA Standard Water Balance Authorized Consumption Billed Authorized Consumption Unbilled Authorized Consumption Billed Metered Consumption Billed Unmetered Consumption Unbilled Metered Consumption Unbilled Unmetered Consumption Revenue Water System Input Volume Apparent Losses Unauthorized Consumption Customer Meter Inaccuracies Non Revenue Water Losses Real Losses Leakage on Transmission & Distribution Mains Leakage and Overflows at Reservoirs Leakage on Service Connections up to metering point Water 12

13 Leakage Types Background leakage Small flow rates, run continuously but not economically recoverable Reported leaks and bursts High flow, reported by customers and get fixed quickly Unreported leaks and bursts Medium flow rates, longest duration and only located by active leakage detection 13

14 Strategy: A Long-term Approach with Immediate [short-term] Benefits Implement IWA best / good practices Pressure Management Unavoidable Real Loss Speed and Quality of Repairs Replacing pipes with least impact on customers Risk-based asset management for maximum return Economic Level Real Loss Current Annual Real Loss Volume Infrastructure Management Active Leakage Control Detecting and fixing leaks Replacing/installing meters (DMAs) 14 Source: The 4 Component diagram promoted by IWA s Water Losses Task Force

15 Current Practice 1. Assessment water balance or water auditing based upon water infrastructures physical data and some statistics 2. Pressure Management Divide the network in Pressure Zones and DMAs Use hydraulic model for PRVs Install PRVs to manage MNF 3. Active Leakage Detection Sounding for leaks Step-testing, smart balls Acoustic loggers (noise correlators) Smart balls Use hydraulic model and measured (Scada) data 15

16 Pressure Management (Case Study in Cyprus) 16

17 Water Board of Lemesos Established in 1951 Semi-government, non-profit organisation Supply of potable water Number of employees : 110 Area served : 100 km 2 Population Served : Annual water needs : 14 million m 3 Number of consumers : Length of pipework : 850 km 17

18 Pressure Management Considerations Pressure range: Between 20m and 40m Minimum of 15 m if conditions allowed Pressure control achieved through: Pressure reducing valves Pressure regulating valves Types of pressure control: Fixed outlet Two point control (Time or Flow) Flow / Time modulation Critical point control 18

19 Pressure Management Objectives Pressure reducing valve (downstream pressure control, open/close capability) Before pressure reduction After pressure reduction Pressure sensor (downstream pressure monitoring) District meter (mechanical Woltman type) Strainer (meter protection) Reduction in MNF Reduce the flow rates (MNF) of all leaks Reduce surges and excess pressures Reduce burst rates and background leakage, cut repair costs Reduce some components of consumption Effects of change can be hydraulically modelled and predicted 19

20 DMAs - Pressure Management DMA categories Small : <1000 properties Medium : properties Large : properties Factors considered in DMAs (re)-design Use Hydraulic Model (WaterCAD) Minimum variation in ground level Single entry point into the DMA Well defined DMA boundaries Area meters correctly sized and located Continuous monitoring 20

21 Pressure Reduction (1/3) DMA 232 before pressure reduction Possible pressure reduction of about 0,5 bar 21

22 DMA 232 Pressure Reduction (2/3) after pressure reduction Reduction in AZP from 39 m to 32 m resulted in reduction in MNF from 5.2 m 3 /hr to 4.3 m3/hr 22

23 Pressure Reduction (3/3) Before pressure reduction After pressure reduction Reduction in MNF 23

24 Minimum Night Flow Summary Results DMA (Sector 2) AZNP (m) Actual MNF (m³/hr) Background losses(m³/hr) Locatable losses (m³/hr) before after before after before after before after ,92 2,16 0,63 0,24 1,88 0, REDUCTION 36 5,69 3,85 3,39 30 m1,65 3 /hr 0,16 0, ,07 2,24 1,53 0,71 0,05 0, ,58 2,56 1,70 0,82 0,35 0,20 (Sector 2) (25%) ,50 2,52 1,68 0,82 2,23 0, ,96 9,78 5,42 2,41 4,16 3, ,04 6,84 5,62 2,55 0,37 0,24 Annual water 38 15,52 saving 10,44 5,91 = 220 3, ,11 m 3 2, ,60 7,20 3,42 3,03 0,51 0, ,06 3,73 1,13 0,96 2,01 1,85 or ,80 18,00 5,57 4,60 9,37 6, ,01 7,92 4,63 3,54 2,17 0, ,17 4,32 1,32 1,05 2,21 1, ,45 3,96 1,48 1,10 1,48 1, ,55 2,44 0,32 0,23 2,26 1,24 Total before 117,92 43,75 34,32 Total after 87,96 27, ,02

25 Leakage Detection using Models and Data 25

26 Mathematical Optimization Techniques r n n n n X = F(X) r ( LNi, Ki ); LNi J ; n = 1,..., N; i = 1,..., LK n n 0 K K Search for: Minimize: Subject to: Leakage Nodes: Where: LN i n n K i nl= i N n= 1 LK n max is the index for leakage node i in group n is emitter coefficient at leakage node i in group n n n J is the set of junctions in demand group n N is the number of demand groups nl is the total number of leakage nodes LK n is number of leakage nodes in group n n K max is the max emitter coefficient for demand group n 26

27 Integrated Framework Leakage Detection & Model Calibration WaterGEMS (Darwin Calibrator) 27

28 Case I: system conditions (United Utilities) DMA system model 12 km pipelines 1000 properties 5 pressure loggers and one flow meter 28

29 Case Study I: previously detection Burst A aa Burst B aa KEY DMA Boundary Leak located Distance from prediction Mains diam BURST A <50m 150mm BURST B Distance from prediction Mains diam 150m

30 Case I: results comparison Burst A & B 30

31 Case I: savings Burst A Saving > 210,000 Euro / year Raw Measured Value for 08016DM01_02 WALTON SUMMIT (1 Apr Jul 2004) Burst B cub. m/hr m 3 /hr reduction 60 Apr 01 Apr 15 Apr 29 May 13 May 27 Jun 10 Jun

32 Case Study I: flow comparison (after) 32

33 Case II: another DMA Field survey Actual Leakage 15 m 3 /hr reduction Savings of 115,000 Euro / year Leakage spots identified with WaterGEMS Leakage Calibrator 33

34 Important: Check Risk on Transients! 34

35 Essential Requirements Build hydraulic model Collect field data (e.g. flows and pressures) Prepare and import data Calibrate the model and make leakage detection runs Analyze results Look for consistent predicted leakage hotspots Go to the filed: check the identified locations and take a proper acction 35