Improving Efficiency of Existing Water Distribution

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cards using one shot mono-stable Multivibrators and solid state relays as a safety measure. A predefined sensor status data packet is generated by the.
Improving Efficiency of Existing Water Distribution Networks by Centralized Monitoring P. G. Jayasekara, D.K. Illangasinghe, J.K. Dahanayake, K. Wickramage and Rohan Munasinghe Department of Electronic and Telecommunication Engineering University of Moratuwa Moratuwa, Sri Lanka Email: {pgj02, dki02, jkd02, kw02, rohan}@ent.mrt.ac.lk reservoirs (or sumps) and pumped to water towers from which demand centers are catered via distribution lines.

Abstract—The optimum distribution of treated pipe-borne water is a critical requirement in countries which have a deficit production in comparison with the demand. However, in 3rd world countries, it is not feasible to design the entire water distribution network as a whole, to enable near-optimized delivery, due to economic constraints. The current practice in such countries is to operate the nodes of the water distribution network, such as pump houses and water towers, in isolation, based on ad hoc criteria. Improper co-ordination of these nodes leads to wastage and inefficiencies in the utilization of the scarce resource of treated water. Hence the challenge lies in improving the water distribution process via a network that has not been inherently designed to support optimum distribution. The proposed system presents a solution to this predicament by centrally monitoring and controlling the functionality of these points of distribution. It is a low cost, locally developed system which can replace the PLC based automation systems currently deployed, simultaneously providing the additional functionality of remote control. It is operable in 3 interchangeable modes: Manual, Auto and Remote. The Remote Mode, which is a novel feature unavailable in the existing system, enables a central server to monitor the operation of the total network and issue supervisory commands to regulate the functionality or even to take over the control of a remote pump house, if necessary. It also facilitates the centralization of skilled labor.

The ideal solution to ensure near-optimal distribution of water would be to address this issue at the design phase of the network. There are many studies already carried out in this regard. Researchers have been especially interested in applying Genetic Algorithms [2], Cross Entropy [3], Artificial Neural Networks [4] and Harmony Search Optimization Algorithms [5] in deciding the design parameters of the network and nearoptimal scheduling of pumps.

I. INTRODUCTION The National Water Supply and Drainage Board of Sri Lanka (NWSDB) is the prime body supplying treated pipeborne water to the nation, catering to an annual demand of 383 million m3[1].

However, in Sri Lanka and other 3rd world countries, the distribution network is designed and constructed in separate segments using foreign funds. This has led to the existence of a system that has not been designed for overall optimization. Further, the nodes of the network are operated as standalone systems, without coordinating with other nodes, leading to several problems. The pump houses are operated according to a predetermined schedule, established on ad hoc criteria, which is an inflexible practice failing to utilize the water available efficiently. This has resulted in demand centers with a lower requirement getting access to treated water, at the expense of those with a higher density and consumption, and also not utilizing a surplus of water when available. The communication with the water tower, to which the water is pumped, is mostly carried out via telephone calls by the in-house staff, which is a cumbersome and inefficient procedure. The lack of data about the real time movement of water in the distribution network makes it impossible to route water in the best possible way according to the real time demand. The absence of a central point of supervision also gives rise to additional drawbacks such as the difficulty to centralize skilled labor for better decision making purposes as they are currently required to be dispersed through out the country at local distribution points.

The treated water is distributed to consumers dispersed over a wide geographical area via the water distribution network. It comprises a variety of nodes such as treatment plants, reservoirs, water towers and pump houses as illustrated in Fig.1. The raw water extracted from rivers is purified to meet standards of drinking water, and distributed via transmission pipe lines. In some occasions, these lines may be tapped directly by distribution lines or a pump house, without an intermediary reservoir. However, in the most common configuration, water from the transmission lines is stored in

The proposed system provides a solution to the above identified problems through centralized control. It has been developed at a significantly lower cost than the available industrial solutions and is operable in 3 interchangeable modes. Auto mode controls the functionality of the pump house according to an algorithm by considering the level variations in the water tower and the reservoir. Manual mode enables the pump house operators to control the functionality through a control panel, and during Remote mode, the complete control of the pump house is taken over by the server operators, who

Keywords—Programmable Logic Controller (PLC), Remote Monitoring, Remote Supervision, Centralized Control, NearOptimal Scheduling

978-1-4244-1900-5/07/$25.00 © 2007 IEEE

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can issue control commands that will be executed directly without the intervention of the in house staff.

II.

THE PROPOSED SYSTEM

The proposed system can be identified as a server-client(s) formation. The clients catered by the remote server are the water distributing pump houses where as the remote server, responsible for monitoring, supervising and controlling all the connected clients, can be located in a regional central location. Apart from the remote server, the system that has been developed resides totally at the pump house, the client, in a newly designed control panel. The system comprises three main functional blocks as to remotely monitor, supervise and control the water distribution nodes and is discussed in two main sub systems, the hardware subsystem and the software subsystem. A. The Hardware Subsystem The microcontroller based Main Board can be identified as the heart of the hardware subsystem, which governs all the three functionalities at hardware level. Together, it integrates all the subunits acting as the central processor. The main board makes use of three microcontrollers, namely the sensor interface microcontroller, the actuator driving microcontroller and the main microcontroller, in order to achieve its functionality. 1) Remote Monitoring: The Sensor interface microcontroller is accountable for the phase of remote monitoring at the hardware level. It is accomplished by means of the sensor data acquisition peripheral cards. These cards acquire sensor data, both analog and digital and then interface them to this sensor interface microcontroller.

Figure 1. The Water Distribution Network

Regardless of the mode of operation, the functionality of the pump house is under the surveillance of the central server operators who can issue supervisory commands to be executed by the pump house staff during all 3 modes. As they are monitoring all nodes of the network similarly, these commands are used to ensure the optimum routing of water. A near-optimal water distribution algorithm integrated with the server application provides a guideline for the decision making process of determining the most favorable method of water distribution. This ensures the achievement of the final objective of optimum water distribution.

A digital data acquisition card has been designed utilizing two-stage 8-1 multiplexing (4051 Mux IC) and is capable of handling 64 digital data inputs. All the digital status data related to the delivery valves and pumps are among the digital data monitored. The number of digital data acquisition cards to be used will depend upon the nature of the pump house, i.e. the number of delivery valves and pumps present at that water distribution node.

Figure 2. The Block Diagram for the Hardware Subsystem

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Analog data acquisition cards form the interface between the industrial 4-20mA current loop analog signals and the sensor interface microcontroller. The monitored analog sensor data are the pump house reservoir level, catered water tower level and the outlet flow reading. The accomplished 0-5 voltages from the cards are analog-to-digital converted and processed further inside this microcontroller. Overload current protection has been implemented in the analog data acquisition cards using one shot mono-stable Multivibrators and solid state relays as a safety measure.

2) Remote Supervision: For the near-optimal distribution of water, the remote server can issue supervisory information to any client so that water can be routed in a systematic and coordinated way. A buzzer is activated to inform the operator at the pump house about the incoming supervisory information. An LCD panel is placed in the implemented control panel to display such commands and warnings, to be seen and to be executed by the operator at the pump house. 3) Remote Control: Remote control phase includes the taking over of the control of the clients by the central server. If the supervisory information had not been executed by the operator, the control of the pump house can be taken into the hands of the central server to drive the necessary actuators that are needed to be driven to achieve near-optimal water routing. Actuator driving at the hardware level is performed by means of an actuator driving circuitry, which is being controlled by the control signals issued by the Actuator Driving Microcontroller, in the main board.

A predefined sensor status data packet is generated by the sensor interface microcontroller and is sent to the client computer placed at the client pump house which runs the client software application. The sensor interface microcontroller also communicates with the main microcontroller via the serial peripheral interface (SPI) bus. The sensor data is transferred and is further processed by the main microcontroller. Together, three LED visual (bar) representations have been implemented at the front of the panel to display the analog levels, driven according to the analog sensor data information obtained. Ultimately, this remote monitoring phase allows the remote central server to have the total picture of the water distribution network.

It first drives a set of DC relays and then the corresponding AC relays attached with the actuators; the delivery valves and pumps. The system block diagram and the implemented system are illustrated in Fig.2 and Fig.3 respectively. 4) Operation Modes This proposed system possesses three modes of operation namely, Manual mode, Auto mode and Remote mode. Any industrial level application having a manual mode of operation is a must; thus, it has been included. The included auto mode of operation is microcontroller based automation where the actuators are run according to the variations of the analog level information of the connected over head tower as well as the temporary reservoir at the pump house that keeps water to be distributed. The new feature of the system is the introduced remote mode of operation. As mentioned earlier, the remote supervision as well as the remote control phase occurs in this mode. To arrive at the remote mode of operation the central server, first, has to make a request to the selected client pump house to take over the control. However, the design is implemented in such a manner that the priority is given to the manual mode of operation, i.e. the request can be overridden by the manual operator by not allowing this transition to occur. This is there not to allow the remote central server to take over the control of the pump house if it is under any maintenance or similar activity, which will force the system to be in perilous situation. So, the operator is being allowed to override the mode change action. Also, smooth transition of modes is addressed in the implemented design. The actuators, in operation, are latched in any transition between modes. 5) Microcontroller Operation The three microcontrollers are delegated a predefined set of operations to be performed and are communicating with each other when necessary. After the initialization, the sensor interfacing microcontroller generates the necessary delimiters

Figure 3. The Implemented System for one Pump House

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to form the sensor data packet to be sent over the serial interface. The algorithm is illustrated in Fig.4.

The main microcontroller, essentially, executes functionality according to the current mode of operation. The Fig.5 illustrates this. In the manual mode of operation, the work load of the main microcontroller is kept at a minimum level. All the operations are governed by manual push button requests. The electrical wiring bypasses microcontroller and directly runs the corresponding pumps and valves. In this mode, the microcontroller only listens to incoming serial data. That is, it repeatedly checks whether the remote server wants the control over the system and does nothing other than that. At a mode change request, the controller first activates the buzzer. Then the microcontroller checks whether the operator, if any, wants to override the request. Had such interrupt not occurred, the controller would change mode to remote by energizing the Remote relay. How this scenario is handled by the main microcontroller is illustrated in Fig.6. In the remote mode of operation, the main microcontroller waits until valid serial data, which is sent from the remote server, is present on the USART interface. Valid instructions are decoded and then corresponding control signals are sent to the actuator driving circuitry to drive the relevant actuators. The algorithm is illustrated in Fig.7.

Figure 4. Algorithm for the Sensor Interfacing Microcontroller

By varying the six control lines to the digital data acquisition card, the microcontroller acquires the status of the corresponding input channel. The obtained value is written to the sensor interface microcontroller memory. The minimum delay needed by the 4051 MUX IC to differentiate between a consecutive sweeps of two channels, is 700 ns (typical) at 5V. Hence, a full digital data acquisition board sweep requires around 45 ms, and the control channels change with around 700 ns intervals. To allow better operation, the microcontroller changes the control channels with 2 ms interval leading to around 130 ms time period for a full board sweep. Analog lines are then A/D converted to be inserted into the sensor data packet. Next, the main microcontroller is updated with the latest sensor information via the SPI data bus. Finally, the sensor interface microcontroller communicates with the client software application via RS232 interface sending the generated sensor data packet. The loop continues infinitely.

Figure 6. Mode transition from Manual Mode to Remote Mode

Figure 5. Algorithm for the Main Microcontroller

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simulated according to the statistics obtained by the NWSDB. In this mode, the operator can change the nodes and their parameters and visualize its effects on the other nodes within a future time period. The decision to route water is determined by assigning a weight to each system node and comparing them. In calculating the weight, the following variables were considered.

Figure 7. Remote Mode of operation



Current water level of the water tower/reservoir



The rate of level variation of water tower/reservoir



The time taken to fill the water tower/reservoir



The last operated time of the pump house/inlet valve



The priority of the demand centre catered by the water tower/reservoir. III.

B. The Software Subsystem The system consists of three software applications. The client application installed in the client PC at the pump house links the hardware system with the server. The server application is connected to all the client pump houses in the region. The expert water routing algorithm runs in parallel with the server application, and will make decisions to optimize the water distribution.

RESULTS AND DISCUSSION

After the continuous testing of the fully integrated system, it was found to be successfully operable in the selected industrial environment (at Maharagama Pump House), proving to be in par with the existing automation system, in terms of reliability. Successful extraction of real time data was observed at the server. A sample of the variation of the flow meter reading at the time of operating two pumps, and the corresponding change in their respective valves, is shown in Fig.8. The issued sequence of the control signals are shown in Fig.8.f. With the control signals, the state changes of the actuators, the delivery valves and the pumps, are shown in Fig.8.b, c, d and e. Fig.8.a depicts how the flow meter reading has changed with state transitions of the actuators.

The developed system is a 24/7 system. The client application receives sensor data from the pump house at a consistent speed. The server application is capable of concurrently processing the client applications and maintaining a steady speed of updating the information from the client (Remote Monitoring). Analog and digital sensor data is represented in graphical forms at both server and client application. In the server application the main GUI gives a summary about all connected pump houses and detailed information is also accessible. The GUI of the software application is illustrated in Fig.9. The server application is capable of issuing supervision and control commands. The client will only forward the recently received control information neglecting delayed ones, providing protection from network malfunctions. In sending the control signals from the client application to the hardware system, retransmission is utilized. This ensures that the microcontroller will take the necessary actions upon the received control signals. The server application has an automatic feedback of the commands it has issued, as remote monitoring is available throughout. The acquired information from the client is stored in a normalized database at the server and data can be retrieved for analysis purpose. The optimum water routing algorithm provides a means for routing water efficiently among the system nodes (pump house, reservoirs and water towers) which extracts water from main transmission lines originating from treatment plants. The algorithm operates in two modes. In the Live Mode, the real demand and supply of the system will be calculated according to the real time data transmitted from each node. In the Simulation Mode, the demand variations in the network are

Figure 8. Results Obtained in the Remote Mode of operation

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Figure 9. The Main GUI

IV. CONCLUSION In this paper, the implementation of a robust system with remote monitoring, supervision and control functionality to optimize the treated water distribution of existing networks was introduced. The client node functionality was fully implemented inside a control panel and the application on the Client PC. The system has been tested under different operating conditions in the industrial environment itself. As future development work, the system is intended to be implanted in several client nodes in collaboration with the NWSDB. The algorithm developed is aimed to be further optimized with the ultimate objective of optimized water distribution in the country.

REFERENCES [1] [2]

[3]

[4]

ACKNOWLEDGMENT This system has been developed by the authors as a constituent of their B. Sc. Undergraduate studies. This work has been carried out with the funding of Sri Lanka Inventors Commission (SLIC) under the grant number SLIC/UOM/GRANT/2006/023.

[5]

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National Water Supply and Drainage Board “Annual Report 2005”, 2005 Artem V. Babayan , Dragan A. Savic , Godfrey A. Walters, “Multiobjective Optimization Of Water Distribution System Design Under Uncertain Demand And Pipe Roughness”, Modelling and Control for Participatory Planning and Managing Water Systems, workshop by International Federation of Automatic Control, Venice, 29 Sept - 1 Oct 2004. Lina Perelman, Avi Ostfeld, “Water Distribution Systems Optimal Design Using Cross Entropy”, Genetic And Evolutionary Computation Conference: Proceedings of the 2005 conference on Genetic and evolutionary computation, 2005, pp. 647 – 648 D. R. Broad, G. C. Dandy and H. R. Maier, “A Metamodeling Approach to Water Distribution System Optimization”, Journal of Water Resources Planning and Management, Vol. 131, No. 3, May/June 2005, pp. 172-180 Zong Woo Geem, “Optimal Cost Design of Water Distribution Networks Using Harmony Search”, Engineering Optimization, Volume 38, Number 3, April 2006, pp. 259-277(19)