In recent years, wireless measurement and control units have become more popular for monitoring water distribution systems in the drinking water supply. Electric power supply for a higher number of devices through fixed connections to the public electrical grid is technically complex and requires large investments. Powering monitoring devices, which are installed in areas where electrical power supply is lacking, is difficult and considerably increases personnel and operational costs due to frequent battery changes. In such cases, harvesting energy from the water distribution systems or the environment would be an attractive option. In this work, an energy-self-sufficient system has been developed to solve these problems. The system transforms, by use of an energy harvester, the kinetic and hydraulic energy of water flow in a pipeline to electrical energy, stores this energy, and uses it via a micro-controller unit for measurements and wireless data transmission to a central server.

INTRODUCTION

To monitor and manage water distribution networks, hydraulic sensors are usually installed in the district inlet pipes to measure water flow and pressure (Khan et al. 2005). The monitoring of flow rates is used to capture and evaluate the functionality of the water system, which results in a reduction of the response and repair times in case of leakage. This includes monitoring of the volumetric flows as a whole or in parts (measuring zones/District Metered Area (DMA)) (Kober 2013). In order to minimize water loss, the International Water Association (IWA) suggests four basic methods of managing real losses (Active Leakage Control; Speed and Quality of Repairs; Pressure Management; Pipeline and Asset Management) (Lambert & Fantozzi 2005).

This conventional ‘water loss management’ can be labor- and cost-intensive. Regular campaigns in the water supply districts are needed to detect an active leak. Nocturnal flow measurements are made at intervals of usually more than a few years. Furthermore, for leak detection purposes, acoustic loggers are used over several days to observe the pipes or fittings.

Some pilot projects showed that the continuous use of leak detection sensors (mostly acoustic sensors) and the demand actuated ‘intelligent’ control of the pressure can considerably reduce the loss compared to that achieved by conventional instruments (Oppinger & Baader 2009; Van Hemert 2012). Since all the units for measuring, controlling, and regulating are electrically operated they require a continuous power supply, which limits extensive use of these devices. This problem cannot be resolved by a connection to the public electricity supply network because of the cost perspectives and, to some extent, legal requirements (e.g., easement of the planning of the route). Therefore, due to the lack of power supply in the district inlet pipes, where the sensors are installed, the conventional powering solution is use of batteries. However, batteries require frequent replacement due to their limited life-cycle, and, in the context of a wireless sensor network, it may also result in substantial maintenance overhead. Furthermore, alternative supplies, such as by using photovoltaic cells or wind turbines in public or urban areas, are difficult to install and not reliable due to the risk of theft and vandalism. By using smart meters, the water loss through leaks can further be reduced and thus has further implication for energy consumption and treatment costs (Britton et al. 2013).

Therefore, it is highly desirable to generate the electricity required for the measurement or control units directly from the ambient environment. Obtaining electrical energy from small energy sources directly available from the ambient environment is often referred to as ‘energy harvesting’. There are several recent studies focusing on renewable energy harvesting from the ambient environment, thus providing a self-powered wireless sensor network (Ye & Soga 2012). The main sources of energy available for harvesting are mechanical energy, light energy, thermal energy, electromagnetic energy, and the human body (Costis & Aliwell 2008). Potential ambient energy harvesting sources and techniques are presented by Costis & Aliwell (2008), Priya & Inman (2008), Yildiz (2009), Carli et al. (2010), Wang & Ko (2010) and Ye & Soga (2012). Mohamed et al. (2011) reviewed and discussed the potential of using power harvesting techniques for monitoring water distribution networks and the work done in the area of monitoring water distribution systems using smart sensor networks. There are two types of energy harvesting sources that seem most applicable in water pipes: water flow and flow-induced vibration (Mohamed et al. 2011).

In this study, we tested energy harvesting systems and evaluated their feasibility for application to water distribution systems. In addition, it was also investigated whether the hydraulic energy harvested directly from the pipeline is sufficient for the operation of measurement and control units.

MATERIALS AND METHODS

System design

The complete system consists of an energy harvester, appropriate coupling to the water distribution network, power management system, a control unit (ControlCom) at the field level (Field Unit), sensors, a telecommunication system with gateway, a Supervisory, Control and Data Acquisition (SCADA) system, and a user interface (Human Machine Interface (HMI)) (Figure 1). A test track was designed and built to test and evaluate the harvester.
Figure 1

The ‘Smart Water Power’ model system with the system components.

Figure 1

The ‘Smart Water Power’ model system with the system components.

Selection and identification of an appropriate energy harvesting technology

Various possibilities have been considered for the so-called ‘energy harvesting’. In this regard, the use of the temperature gradient is theoretically possible. However, the main limitation is the climatic and meteorological conditions (seasons) in Central Europe that do not allow a continuous and effective securing of the temperature gradient. The concept of vibration harvester was also excluded because it appeared to be unfeasible in the framework of the project (disadvantage: strong cross-sectional narrowing of the line, along with a significant pressure loss). For this reason, the focus was given to testing and examining a practically possible harvester system based on flow.

Power generation from fluid and gas flow confined in pipelines is not a new concept. In the past, much work has been done, particularly in the area of pressurized gas flow (Hoffmann et al. 2013). A digital and battery-free smart pipe-flow-meter was developed at the Kun Shan University. Feasibility of this device was demonstrated through repeated experiments performed for air flowing in an 11 mm diameter pipe; 18 s of energy harvesting at 10 revolution-per-second (RPS) turbine speed generated enough power for the flowmeter to operate for 720 s at 20 RPS, without battery or any other external power (Hao & Garcia 2014). Hoffmann et al. (2013) presented a rotational, radial-flux energy harvester incorporating a three-phase generation principle for converting energy from water flow in domestic water pipelines. The energy harvester was able to generate up to 720 mW while using a flow rate of 0.33 L/s (fully opened water tab).

In this study, a micro-turbine from the company Kinetron (The Netherlands) was used (Figure 2). This turbine has been used in numerous applications (e.g., powering electronic and sensor devices of gas and pressure reducing valves), and consists of materials that are compatible with drinking water, and have corresponding drinking water certificates such as KTW (Guideline for Hygienic Assessment of Organic Materials in Contact with Drinking Water) and WRAS (Water Regulations Advisory Scheme) (Cla-Val 2013; Kinetron 2015).
Figure 2

The micro-turbine WTG3250 (left) and the prototype of a specially developed harvester (right).

Figure 2

The micro-turbine WTG3250 (left) and the prototype of a specially developed harvester (right).

Embedding a turbine directly into the main pipe of the water distribution system is not recommended because it might disturb the main supply cycle and there is the risk of the device falling off into the main pipe (Ye & Soga 2012). Therefore, the WTG3250 was placed in a bypass pipe. In addition, a specially developed prototype was tested (Figure 2). The harvester prototype consists of the propeller, a three-phase alternator and a carrier device for installation directly in the main pipe.

System requirements, computational fluid dynamics (CFD), installation of test track

To simulate the use of the harvesters in a real drinking water system, the conditions and operating parameters in water distribution networks need to be identified. In a literature review, appropriate boundary conditions were collected and taken into account for the construction of a test track.

The amount of energy that can be generated from flow in a pipe is a function of several parameters including efficiency of the power harvester in converting ambient energy to electrical energy, pressure, the pipe geometry, and flow and water velocity depending on consumption behavior. For the economical dimensioning of water supply pipelines, the flow demand and water velocity are crucial. The economical water velocity (Figure 3) is a function of the pipe diameter and is specified within 0.5 to 1.5 m/s limits (Fritsch et al. 2014). To simulate the temporal distribution of water velocity in the pipe, measured flow rates of a water utility (municipal utilities Augsburg) were used, and converted into the water velocity. The graph in Figure 4 shows the time course of the water velocity in a pipe (diameter (DN): 250 mm).
Figure 3

Design values for economical water velocities in drinking water distribution networks.

Figure 3

Design values for economical water velocities in drinking water distribution networks.

Figure 4

Time course of the water velocity in a pipe.

Figure 4

Time course of the water velocity in a pipe.

For the design and operation of the test track and for proving the energy harvesters, the following operating parameters were defined:

  • ▪ Minimum water velocity in main pipe of 0.05 m/s.

  • ▪ Maximum water velocity in main pipe of 2.7 m/s.

  • ▪ Network pressure between 2 and 8 bar.

  • ▪ Main pipe diameter: 80 mm.

  • ▪ Bypass pipe diameter: 20 mm.

For experimental characterization, the energy harvesters were connected to a conventional domestic water pipe line. The generated voltage and power output were recorded. In addition, the installation of the WTG3250 required a test stand configuration. For this reason, a bypass system with DN 20 was installed for the test track (Figure 5).
Figure 5

Setup of the test track.

Figure 5

Setup of the test track.

The application of a flow simulation with CFD is particularly relevant to the bypass construction that includes the WTG3250. By using CFD, it was possible to demonstrate, at a model level, whether built-in components in the main pipe have an impact on the operating conditions in the system. The main task was to measure the current velocity and the pressure drops in response to changing flow rates and various fixtures. The fixtures in the main pipe were required to get sufficient flow in the bypass.

Power management – development of a power board

The development of a power management system was required to supply the field unit, the sensors, and the telecommunication unit with electrical power (generated by the energy harvester). The main function of the power management system was to regulate the supply voltage and to generate a constant voltage independent of source or load variations. Furthermore, the power consumption of the application devices needed to be minimized by power management so that maximum functionality, performance, and operation time could be achieved with the minimum energy provided by the energy harvesting module (Costis & Aliwell 2008). The developed power management system consisted of a rectifier package to convert the AC voltage generated by the energy harvester to an unregulated DC voltage, a charge controller, which generated the required voltage to charge the selected energy storage, the energy store itself (battery or high-performance capacitor), and DC/DC converters providing the voltages required for the consumers.

Control-and-communication unit with sensor

The tasks of the control-and-communication unit (ControlCom) were: monitoring the harvester/generator, the power management unit, performing measurements by sensors, caching the data, and wireless transmission of the data to a gateway for transmission via the Internet to the SCADA system. The hardware of the ControlCom system was based on a microcontroller. The system was equipped with a Real Time Clock (RTC), a Secure Digital Memory Card (SD) storage unit and a serially read-out temperature sensor with individual identification. The ControlCom board was powered by the power board. For wireless communication, a ZigBee gateway module was used, which is a wireless networking standard targeted at monitoring, control, and automation of building and home (Walawalkar et al. 2010; Huang et al. 2011; Batista et al. 2013).

Telecommunication, gateway, Internet

The exchange of data between units in the pipeline network and a server was implemented through a gateway concept. This concept required at least two wireless transmission links, between the installed units in the pipeline network and the gateway and between the gateway and an access point to the Internet. The gateway was initially equipped with a WLAN module that was subsequently replaced after efficiency analysis by an Ethernet interface. The wireless communication, therefore, was converted to ZigBee. The gateway was built on the same hardware platform as the ControlCom board. In addition to the ZigBee module, a LAN module to communicate with the server via the Internet supplemented the board.

SCADA and HMI

A simplified SCDA system was developed for the transfer of the measured data, their storage and also for evaluation and storage of system configurations. The ControlCom unit transmitted the data to a web server. The data were transferred via PHP script to a Structured Query Language (SQL) database system and stored therein. Only simplified interfaces were developed and used to provide access to the ControlCom unit and the database server. Direct access to the ControlCom unit could be obtained via a USB port of the microcontroller in connection with a monitoring program installed on a PC.

RESULTS AND DISCUSSION

The frequency of the generator and the generated electrical power of the harvester depend on water velocity (almost linear), the harvester type and the test track configuration. The flow studies and CFD showed that significant energy harvesting from the WTG3250 can be expected only with a significant reduction in the diameter of or by closing the main pipe. There was no flow in the bypass without some modifications in the main pipe. This was also verified by the theoretical model calculations by Ye & Soga (2012) and the first test experiments without any fixtures in the bypass (Figure 7, upper left graph). CFD further showed that even a reduction in the diameter of the main pipe with a flow restrictor (orifice with 30 mm) caused no significant increase in the water velocity in the bypass (Figure 6). This fact has been taken into account for further investigations regarding WTG3250. A ball valve, which can close the main pipe from 0% to 100%, was installed into the main pipe (Figure 7). If the main pipe is completely closed, the water velocity in the bypass pipe can reach 1.2 m/s (Figure 7, lower panel).
Figure 6

Water velocity in the bypass at 4-bar pressure with CFD.

Figure 6

Water velocity in the bypass at 4-bar pressure with CFD.

Figure 7

Water velocities in the main and the bypass pipe at 4-bar pressure using a ball valve.

Figure 7

Water velocities in the main and the bypass pipe at 4-bar pressure using a ball valve.

Assuming the principle of steady flow, the power generated by the turbine can be expressed by (Benson 1995; Munson et al. 2006): 
formula
1
where 
formula
2
= kinetic energy; = time; = power generation efficiency of the turbine; = mass of the water; = water velocity through the pipe; = water density; = volume; = flow rate in the pipe; = internal cross-sectional area of the pipe; and = radius of the pipe. Substituting Equation (2) into Equation (1), the power generation can be expressed as: 
formula
3
The water is considered to be incompressible; therefore, the principle of steady flow to a parallel can be applied. The bypass pipe is assumed to make no disturbance to the water pressure and velocity in the main pipe. The water velocity in the same stream can be calculated with the energy equation of Bernoulli (Mott 2006; Munson et al. 2006): 
formula
4
where and are the pressure at point 1 (inlet point to the bypass pipe) and point 2 (outlet point to the bypass pipe); and are the height of the two systems . is the head loss and can be given as (Munson et al. 2006): 
formula
5
where = friction factor; = length of the small pipe; = radius of the small pipe; = main loss coefficient caused by the friction of the straight pipe; and = secondary loss coefficients caused by other components in the pipe such as elbows, the entrance, and the exit. Since the power generation efficiency in Equation (1) is considered to include the loss caused by the micro-turbine, its loss is neglected (for the theoretical approach). As equals the energy equation can be simplified as: 
formula
6
Finally, the water velocity through the bypass can be simplified as: 
formula
7
With the help of the theoretical approach of Ye & Soga (2012) and the measured values from experimental series, a comparison might be possible (Table 1).
Table 1

Water velocity and harvested power from the bypass pipe system, adapted after Ye & Soga (2012) 

Water velocity (m/s) theoreticalElectric power (mW) theoreticalWater velocity (m/s) test trackElectric power (mW) test track
0.27 0.32 0.32 500 
Assumptions (Ye & Soga 2012)Configuration test track (main pipe closed)
Diameter main pipe 200 mm 80 mm  
Diameter bypass pipe 20 mm 20 mm  
Length of the bypass pipe 100 mm 1,500 mm  
Flow rate 10 l/s 0.1 l/s  
Friction coefficient bypass pipe 0.02 0.04  
Elbow loss 0.2–0.05 0.55  
Entrance loss 0.2–0.5 0.5  
Exit loss 0.5  
Loss caused by the micro-turbine neglected 390 (caused by pressure drop of 40 kPa)  
Loss caused by sensors neglected neglected  
Pressure in the main pipe 4.6 bar 4 bar  
Pressure difference (p1 and p2) 63 Pa 40.26 kPa  
Efficiency of the energy transformation 10% not specified  
Water velocity (m/s) theoreticalElectric power (mW) theoreticalWater velocity (m/s) test trackElectric power (mW) test track
0.27 0.32 0.32 500 
Assumptions (Ye & Soga 2012)Configuration test track (main pipe closed)
Diameter main pipe 200 mm 80 mm  
Diameter bypass pipe 20 mm 20 mm  
Length of the bypass pipe 100 mm 1,500 mm  
Flow rate 10 l/s 0.1 l/s  
Friction coefficient bypass pipe 0.02 0.04  
Elbow loss 0.2–0.05 0.55  
Entrance loss 0.2–0.5 0.5  
Exit loss 0.5  
Loss caused by the micro-turbine neglected 390 (caused by pressure drop of 40 kPa)  
Loss caused by sensors neglected neglected  
Pressure in the main pipe 4.6 bar 4 bar  
Pressure difference (p1 and p2) 63 Pa 40.26 kPa  
Efficiency of the energy transformation 10% not specified  
Figure 8 shows the typically generated electric power at several flow rates at a 150 Ohm resistor. A comparative illustration of the manufacturer's data (left) and the measured values from the test track (right) is given in the same figure. To start the micro-turbine rotations, a flow rate >0.01 L/s is necessary in the bypass pipe. At a flow rate of 0.0083 L/s the turbine stops. The measured data relating to the electric power can be compared to the manufacturer's data and therefore are plausible. The slight deviation between the manufacturer's and the measured data at the test track is a result of the different test settings and operating pressures.
Figure 8

Generated voltage and harvested power of the WTG3250 depending on the water velocity and flow rate; left: manufacturer's data, right: test results.

Figure 8

Generated voltage and harvested power of the WTG3250 depending on the water velocity and flow rate; left: manufacturer's data, right: test results.

The WTG3250 can generate 500 mW at a flow rate of 0.1 L/s and with a typical pressure drop of 40 kPa. The electric power generated for a certain operating time is sufficient for powering the ControlCom unit (Table 2).

Table 2

Energy balance WTG3250 and ControlCom board

Average power consumption ControlCom board over a day (mW)Flow rate (L/s)Hours of operation (h/d)Average power harvesting over a day (mW)Excess power (mW)
1.6 0.25 108 92 
Average power consumption ControlCom board over a day (mW)Flow rate (L/s)Hours of operation (h/d)Average power harvesting over a day (mW)Excess power (mW)
1.6 0.25 108 92 

The efficiencies of the energy harvester systems as a ratio of the electric output power to the hydraulic input power are shown in Table 3. To determine the hydraulic input power, the system boundaries are set between pressure sensors p1 and p2 (as shown in Figure 5). The hydraulic input power can be expressed as: 
formula
8
where 
formula
9
= hydraulic input power and = pressure difference caused by main losses, secondary losses and pressure drop of the energy harvester system.
Table 3

Energy efficiencies of the tested harvesters

ParameterWTG3250Harvester prototype
Diameter pipe 20 mm 80 mm 
Length of the pipe 1,500 mm 2,000 mm 
Flow rate 0.1 L/s 8.04 L/s 
Pressure difference 40.26 kPa 1.48 kPa 
Hydraulic input power 4,026 mW 11,880 mW 
Measured electric output power of the harvester system 500 mW 65 mW 
Efficiency 12.42% 0.55% 
ParameterWTG3250Harvester prototype
Diameter pipe 20 mm 80 mm 
Length of the pipe 1,500 mm 2,000 mm 
Flow rate 0.1 L/s 8.04 L/s 
Pressure difference 40.26 kPa 1.48 kPa 
Hydraulic input power 4,026 mW 11,880 mW 
Measured electric output power of the harvester system 500 mW 65 mW 
Efficiency 12.42% 0.55% 

The efficiency of the WTG3250 (12.42%) is in the range of other investigated harvesting technologies (5–40%). The very low efficiency of the harvester prototype (0.55%) is due to the fact that the flow resistance must be very low. A high pressure drop increases the output electric power and the efficiency, but also causes higher pressure and energy losses that are not suitable for the operation of the water distribution system.

The prerequisite for electric power generation with the WTG3250 is a sufficient flow rate in the bypass pipe, which can be achieved by the closing of the main pipe. However, for operational and technical reasons, it is not possible to close the main pipe and build such a bypass construction in a real water distribution network. For this reason, the use of such micro-turbines is probably limited to applications in domestic installations. In the theoretical approach, the bypass system utilizing the pressure drop to drive the micro-turbine can generate electric power up to 0.32 mW. The pressure drop in the bypass systems may be too low to drive a commercial micro-turbine (Ye & Soga 2012). Therefore, the harvesters that are suitable for use as flow machines (low flow resistance) must be incorporated into the main pipe. In this case, installation techniques such as tapping fittings need further improvement.

The implications of the harvester units for service delivery in water distribution systems are not discussed in this study in detail. The micro-turbine (WTG3250) fulfils the requirements of the KTW Guideline, but it is inapplicable for installation in a main pipeline. However, the materials of the harvester prototype were not examined concerning the KTW Guideline. This harvester was designed such that the construction components are not removed by continuous water flow. To evaluate the suitability of the harvester systems for practical application in water distribution networks in detail, further tests need to be performed with a focus on the pressure losses caused by the harvester systems.

Owing to the difficult installation conditions in the case of the bypass system, the investigations presented here were focused on the specially developed harvester prototype embedded directly in the main pipe.

The electrical power generated by the harvester prototype was 0 to 65 mW at water velocities from 0.1 to 1.6 m/s. The generated power and frequency are shown in Figure 9.
Figure 9

Generated effective power of the harvester prototype and frequency of the generator depending on water velocity.

Figure 9

Generated effective power of the harvester prototype and frequency of the generator depending on water velocity.

The energy demand of the ControlCom unit still needs to be optimized and the energy efficiency of the complete system must be increased respectively.

To determine the current consumption of the ControlCom board, the voltage was gripped with a 560 mΩ sense resistor. Thus, the electrical current flow over time was determined. By summation of the partial currents, the current consumption of the used ControlCom board could be determined with equation (Meyer 2012): 
formula
10
where = root-mean-square current; = summation index; = number of equally spaced measurement intervals; and = voltage.

Considering only the operation, the current demand is 23 mA, and the quiescent current is 1 mA. The power board can supply the ControlCom unit for 210 hours without recharging. The ratio of charging current and current demand amounts to 187%.

Figure 10 shows the current consumption of the ControlCom unit over time. The graph shows the rest periods (>1 mA) and the intervals in which the current consumption is measured and transmitted (about 55–60 mA). In this graph, shorter rest periods are chosen; however, in reality, they are longer and push the current average consumption to less than 10 mA.
Figure 10

Current consumption of the ControlCom board.

Figure 10

Current consumption of the ControlCom board.

The charge controller requires only 53% of its maximum charging current in order to supply the ControlCom board. It is thus possible to supply the sensor unit and to charge the batteries. In addition, a transmission interval of 8 s is not realistic, and in practice, 30 to 300 are required as a rule. As a result, the power consumption is reduced even further.

An estimation of the power consumption of commercial flowmeters revealed that the energy consumption of the devices and the transmitter for flow measurement, in most cases, is in the range of 0.3 to 25 W. The energy harvesters that have been developed and studied in pursuit of this project cannot provide this amount of power.

The electrical power generated by the tested harvesters is in the milliwatt range. At present, the energy yield is not sufficient and it is still too low for the operation of commonly used sensors, such as magneto-inductive flowmeters or ultrasonic flowmeters. However, the energy yield is sufficient for data transmission and the operation of a temperature sensor.

CONCLUSION

The experiments showed that the developed harvester systems can operate continuously. Thus, the application and operation of energy-self-sufficient measurement and control units in water distribution networks are possible. The developed harvester is able to supply up to 65 mW with a water velocity of about 1.6 m/s.

A harvesting system especially for low flow rates with very low voltages requires new micro-generators, the use of active rectifiers, and efficient charge controllers. In this respect, the design of the power characteristic of the energy harvester becomes an important step in line with further device optimization. One of the main challenges for powering smart sensor networks from power harvesters is to optimize the performance of the sensor according to the variation of the harvested energy over time. However, the tested harvesters are not at a stage that their commercial production can be undertaken, and they need further improvements to be adapted to ambient conditions in water distribution networks. These adaptations can be done as a part of new device development for the measurement of pressure, temperature, flow, and acoustic monitoring of distribution networks (leak detection). In future devices, special tasks, such as condition monitoring or online quality monitoring (e.g., demand actuated cleaning and disinfection), are conceivable. In particular, ‘smart grids’, as they are used in electrical power distribution networks, could be possible in the field of water supply.

ACKNOWLEDGEMENT

The authors gratefully acknowledge the financial support of the Federal Ministry of Education and Research Public Relations Department.

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