Pump Asset Operation

8/7/2019 Pump Asset Operation

1/27

The International e-ENGDET 2004 Conference

1

Pump Asset Operation andPerformance MonitoringOver the Internet

Karl J Darbyshire

Geoff Waterworth

Dave Webb


2/27

2

Introduction

Throughout the water industry many methodologies havebeen adopted to enable significant energy cost reductionincurred by Water Pumping Station (WPS)

Refurbishing worn equipment.

Using highly efficient motors. Employing the most efficient pumps. Ensuring water is pumped through the smallest hydraulic head.

Using internet technologies, power, flow and pressureproduced by individual pumps can be monitored over the

Internet, allowing pump operators to remotely selectefficient pump combinations.


3/27

3

Objective

Provide a cost effective method of pumpasset operation and performance

monitoring over the Internet

To provide hydraulic engineers with securereal-time pump characteristics.

Monitor characteristics of individual pumpsevery fifteen-minutes over the internet.


4/27

4

Structure

The presentation is segregated into four keyareas:

Water Supply System. Pump Modelling. Web Technologies. Results. Conclusion.

Further Work.


5/27


5

Water Supply System


6/27

6

Process Schematic

Chemical Treatment

Low Lift Pumps

Gravity Filters

River

Clean Water

Pumping Station

Water Supply System


7/27

7

High-Lift Pumps


8/27

8

High-Lift Pumps cont.


9/27

9

Water Supply System

Water Supply System

Clean

Water

Bypass Valve

P1

P5

High Lift Water Pump

Station Consisting of 5

Fixed Speed Pumps

Extracts Clean Water

from Nearby Storage Tank


10/27

10

Water Supply System

RTU

Data

Data

Analysis

Data

Validation

DataStorage

P1

P5

P2

P3

P4

WPS SCADA

Data Transfer Using

RTU (Out stations)

Micro-Controller

Processors log pump

parameters flow, power

and pressure on the

delivery side of the pump


11/27


11

Pump Modeling


12/27

12

Pump Modelling

H = Delivery Head (m)

Q = Flow (m3/s)

P = Power (kW) = Efficiency

g = Gravity (m/s2) = Density of Fluid (kg/m3)

QHgP

Pump Modeling


13/27


14/27


14

Web Technologies


15/27

15

Java Server Pages (JSP)

JSP is a web scripting technology similar to Microsoft

Active Server Pages (ASP) and Netscape Server Side

Java Script (SSJS)

JSP is a presentation / representation layerenabling users to mix static HTML content with

server side scripting to produce a dynamic output.

JDBC allows the user to interact with the

remote database, which is isolated on the serverside, through SQL statements.


16/27

16

2-tier Client/Server

JDBC

Database

Client Server

Beans


17/27


17

Results


18/27

18

Results

The results illustrate that the web server canremotely accessed pump characteristics to eitherlog, view or delete pump data.

Operating pumps at their maximum efficiency,potential energy cost reductions are achievable.

The stored data may be used in the development ofa sophisticated scheduling scheme or to providehistorical information for water demand prediction.


19/27

19

Pump Data Selection GUI


20/27

20

MYSQL Server Entries


21/27

21

Request Table Data


22/27

22

Pump Modelling

Pump efficiency curves have beenderived to enable pump engineers toidentify inefficient pumps andshortfalls.


23/27

23

Pump Modelling

0 100 200 300 400 500 6000

20

40

60

80

100Pump Curve Characteristics

Volume Flow (Q cubic m/hr)DeliveryHead(Hm)&PumpEfficiency(n%)

WPS1:

88.3 % Efficiency @325 m/hr

74.1 psi Head Pressure @325 m/hr

H v Q

0 100 200 300 400 500 600100

150

200

250

300

350

Volume Flow (Q cubic m/hr)

PowerReq

uirment(PkW)

WPS1:

267.2 kW @325 m/hr

P v Q


24/27

24

Conclusion

A cost effective method of pump assetoperation and performance monitoring overthe Internet.

The combined web methodologies of Java,JSP and SQL technologies provide anefficient and accurate process of secure

remote logging of pump data.

Conclusion


25/27

25

Next Logical Step

Adaptive System- Decision support system

Pump Scheduling.

Equal Pump Combinations to ensure even wear.

Demand Prediction.

Intelligent software to forecast consumer demand.

Further Work


26/27

26

Decision Support System

Alarms

Pumps

Available

Pump

CharacteristicsRequired

FlowData

ValidationPump

Scheduling

Demand

Predictor Archive

Pump

Trends

ManualPrediction


27/27

27

Questions ?

Pump Asset Operation

Documents

Transcript of Pump Asset Operation