This document summarizes several work packages and deliverables related to pressure management. It discusses developing optimization algorithms to define optimal pressure zones and control schemes. It also covers integrating pump control with pressure control to minimize treatment and energy costs while maintaining good customer service and leakage. Case studies will apply these methods to real networks in Harrogate and Oldham.

1. RPA2 – Pressure Management RPA 2 Pressure Management University of Leicester WP 2.1 Redesign of press. schemes Exeter WP 2.2 Feedback control schemes Leic./De Mont. WP 2.3 Control Algorithms Leic./De Mont WP 2.4 Supervisory control scheme Leic./De Mont. WP 2.5 Integration of Pump Control De Montfort WP 2.6 Leakage & Burst Monitoring Leic./De Mont . DELIVERABLES

2. (Re)Design of Pressure Control Schemes RPA2 Work Package 2.1 Haytham Awad

5. GUI dialog

9. (Re)zoning algorithm

10. 33 Tree - 13 Connected - 37 Closed Example

11. Optimal steady state pressure control Hossam AbdelMeguid

15. Technical developments

16. Technical developments

17. Command-line FINESSETools E067.pcm  Technical developments All other applications Read / write 800xA PGIM Read / write HDA / DA FINESSE modules, e.g Pressure Control, Pump Scheduling, Demand Prediction OPC clinet tool

20. Dynamic pressure control Bogumil Ulanicki

22. NEPTUNE Workshop Esholt Hall, 9th July 2008 PID controller uses only pressure measurements Previous work

23. NEPTUNE Workshop Esholt Hall, 9th July 2008 Modified controller uses information about both the outlet pressure and the valve flow. Recent technical developments

27. Test rig experiments on Aquai-Mod controller Piotr Skworcow, Hossam AbdelMeguid (DMU) David Hurley, Mark Lock (Aquavent)

31. Test set-up

33. Preliminary measurement results The measured flow modulation curve

35. Combined energy and pressure management Hossam AbdelMeguid, Peter Bounds, Piotr Skworcow , Bogumil Ulanicki

37. Purpose Minimize cost of water treatment and pumps energy usage whilst supplying good service to customers without unnecessarily high pressure Integration and co-ordination of pump control in grid with pressure control of DMAs Pump scheduling Pressure control Combined energy and pressure management Calculate time schedules for treatment works, pumps, valves, reservoirs and PRV setpoints

38. Proposed Solution Formulate as optimisation problem; cost function: Total cost of water treatment and pumps energy use Inclusion of PRV model – setpoint as decision variable Network model with pressure dependent leakage: Excessive Pumping High energy cost High pressure Increased leakage More water from sources and to be pumped £ £ £

39. Implementation Embedded into the FINESSE software