SMART GRID SMART CITY - CHALLENGES FOR INTEGRATING SMART WATER METERS

SMART GRID SMART CITY - CHALLENGES FOR INTEGRATING SMART WATER METERS Corinna Doolan 1 and Robert Crissani 1 1. Sydney Water, Sydney, NSW, Australia ABSTRACT In 2010, Sydney Water joined Ausgrid to participate in the Smart Grid Smart City trial (SGSC), to assess the issues and benefits of an integrated water and electricity Advanced Metering Infrastructure (AMI). Sydney Water conducted a Smart Water Meter trial from June 2013 to February 2014 as part of the larger SGSC trial, in the local government areas of Ku-ring-gai and Auburn. In total, 135 single dwelling properties had a smart water meter installed to provide a comprehensive record of household water consumption. There were significant challenges around the setup and performance of electricity and water meter wireless communications technology. Product immaturity and interoperability became constraints with the difficult development of the AMI interface and resulted in data and functionality limitations for the smart water meter. These resulted in reduced troubleshooting capability when problems were encountered, a more complex commissioning process, lost data when meter transmissions were missed and limited leak alarm functionality. The Zigbee Smart Energy Protocol (SEP 1.1 open standard) provided communications between the water and electricity meters at 2.4GHz however its radio performance was restricted in the trial in part due to the smart electricity meter s internal Zigbee antenna. While the Smart Water Meter trial participants increased their drinking water use, on average, by five litres a day (1%) when compared to the control group, some individual participant groups actually saved water during the trial period. However, the data interpretation was limited due to the small sample size, short duration of the trial and lack of active participation by the customers. In the detection of household leakage, 42% of the smart water meters had a leak alarm triggered however, there was difficulty in distinguishing between constant and intermittent leaks from the meter data received due to gaps in the hourly reporting consumption data and missing ad-hoc alarms due to off-line water meters. Subsequent site audits identified actual leaks and in many cases, multiple leaks. INTRODUCTION The SGSC trial was the largest national trial to date on integrated electricity and water AMI in Australia. The Smart Water Meter trial was part of the Customer Applications Program, a subset of the SGSC trial. While the SGSC trial involved over 7000 participants, the Smart Water Meter trial was significantly smaller with 135 participants (135 drinking water meters and 20 recycled water meters). The smart water meter was connected to Ausgrid s AMI to automatically read, collect and transfer the water, electricity use and event data to Sydney Water s back office and existing Hydstra database (refer to Figure 1). Participating customers were able to receive their household water consumption data on an hourly, daily, weekly or monthly basis from the customer web portal (refer to Figure 2). Customers were also alerted to any potential leaks by way of a message on the portal. This was in addition to the electricity usage data they were already receiving as part of the SGSC trial. The main objectives of the Smart Water Meter trial were to: determine the issues and benefits around the integration of a joint water and energy AMI investigate customer behaviours in response to receiving near real-time data in terms of their water consumption gain a better estimate of household leakage within the trial and automation of leak detection. THE TECHNOLOGY The challenge was to design and integrate the smart water meter with the electricity Smart Grid AMI functionality to meet the requirements of the customer web portal, hourly water meter data and alarm reporting. The Smart Grid electricity meter used ZigBee communication to connect to the smart water meter and 4G/WiMax (fourth generation/ Worldwide Interoperability for Microwave Access) communication to connect to Ausgrid s back office system. The management of the meters and the meter data was managed by the GridNet PolicyNet system (which was the Meter Management System (MMS)). The integration between ZigBee and PolicyNet was an important part of the design as it

limited the functionality and data that ZigBee was intended to provide for the smart water meter. The Elster V200 digital water meter was selected for the trial. It is a 20mm mechanical positive displacement meter with a battery operated electronic register LCD (liquid crystal display) and integrated two way wireless (ZigBee) communications module operating at 2.4GHz. The smart water meter alarms were managed within the meter s electronic register and comprised of low battery, magnetic tamper, no flow, leaks, check meter and reverse flow alarms. QUANTITATIVE RESEARCH METHODS The quantitative research involved the analysis of hourly water consumption data to determine the transmission performance, reliability and data accuracy. The water meter event data and subsequent alarms were analysed for a shorter duration between September 2013 and January 2014 (once the system was fully commissioned and operational). Sydney Water s quarterly consumption data was also analysed to compare trial participants to similar households that did not participate in the trial (control group). Customers who were participating in the SGSC trial but not the Smart Water Meter trial were also compared in terms of their water use both before and during the trial period. The analysis of the customer web portal data focussed on the uptake and portal use by customers who had a smart water meter installed. Portal access was monitored from December 2012 (electricity meters installed) to February 2014, although the smart water meters were only installed between June and August 2013. This information was valuable in supporting the qualitative research to help understand how often customers interacted with the portal and the potential impact that had on their water use behaviours. QUALITATIVE RESEARCH METHODS The qualitative research was conducted to complement the quantitative data that was collected throughout the trial. The social research involved an online survey which focussed on gaining an understanding of their experiences with the new technology, their expectations of the trial and their attitude towards using water more efficiently. The emphasis on this research was to determine if the participants behaviours had changed - and to what extent - as a result of being provided with detailed and timely information on their water and electricity use. RESULTS Recruitment Numerous recruitment approaches were undertaken which included emails, phone calls, letters, messages on the customer web portal and face to face. Customer uptake reached 228 however, numerous properties had to be excluded due to either property or radio communication issues which rendered them unsuitable to participate, bringing the final number down to 135 properties (40% loss of customers). Participant Survey The total number of participants that completed the online participant survey was 61 (45%). A summary of the key survey findings included: Participation in the SGSC trial was a key driver for customers willingness to then participate in the Smart Water Meter trial. 66% of respondents indicated that their experience had been negative mainly due to missing or incorrect water use data on the portal. Only 15% of respondents believed that their water consumption had reduced since they accessed the customer web portal compared to 48% who believed that their electricity consumption had reduced. Smart Water Meter Performance Issues There were several causes of the smart water meters going offline and/or not reporting data. These included ZigBee and 4G/WiMax signal strength, problems with the MMS, issues with the electricity meter radio communication modules, the water meter leaving the network and not being able to restore the communication link automatically and problems with the water meter battery. Due to the design and choice of infrastructure implemented, the smart water meters had an inherent dependency on the reliability of the smart electricity meter radio communication. There was no data storage capability in the electricity meter and as a result the smart water meter readings were lost when the smart electricity meter went offline. In total, 81% of the smart water meters required some form of remediation to re-establish communications during the trial, either remotely or onsite. Data Transmission Reliability and Accuracy The smart electricity meter provided hourly data more consistently (86% transmission rate) than the smart water meter (61% transmission rate). To assess the accuracy of the meter reading data reported by the smart water meters, the smart water meter readings were compared against Sydney Water s quarterly manual meter readings collected within the same period. Despite the slight discrepancies in the meter reading methods and timing, the correlation for the readings analysed

was significantly high with an R 2 value of 0.9987, indicating a high level of data accuracy reported by the smart water meter. Event Data and Alarms Of the six possible alarms, only the leak detection and reverse flow alarms were triggered across 57 properties. Forty two per cent of all the smart water meters had a leak alarm triggered, with 33% of the smart drinking water meters and 50% of the smart recycled water meters. The reverse flow alarm was triggered on 8% of smart drinking water meters. To have greater confidence and understanding of the leak alarms being generated by the water meter, site audits were carried out by a plumbing contractor. Twenty five properties were inspected and 54 leaks were identified, with 62% of properties having multiple leaks. The leakage rate measured on site varied from 0.06L/hr to 90L/hr and the total leakage for the 25 properties was 944L/hr. Most leaks (46%) were from toilet cisterns. The site audits also verified that leaks were identified at 15 properties that did not have a leak alarm triggered on the customer web portal but where an overnight constant base flow was calculated from the hourly consumption data. The smart water meter (which monitors water use over 24 hours) may not have triggered a leak alarm due to intermittent water use or the alarm was missed when it was not connected to the AMI communication system. Water Use The results of this analysis needs to be interpreted with caution and may be skewed as the Smart Water Meter trial participant properties, already had lower average water use when compared to the control group, before the trial. This could suggest that the Smart Water Meter trial participants had already adopted some water saving type behaviours prior to the trial. The breakdown of results also reveals that some individual trial participant groups actually saved water during the trial period. These results are summarised as follows: Based on the data available at the time of the analysis, Smart Water Meter trial participants increased their drinking water use, on average, by five litres a day (1%) when compared to the control group. The SGSC trial participants with only a smart electricity meter reduced their water use by an average of 2.5% compared to the control group. This may reflect their efforts to reduce electricity use by changing the way they used water using appliances (such as dishwashers, washing machines) or it may be due to their higher drinking water use prior to the start of the trial. These participants may have had more ability to adopt new efficient behaviours around both electricity and water use. The survey data (total 61 respondents) shows that the nine respondents who thought the Smart Water Meter trial helped them save water reduced their water use by about 14% on average. Those that perceived the trial did not have an impact (32 respondents) reduced their water use by 13%. However, those that were unsure (20 respondents) of the Smart Water Meter trial s impact increased their use on average by 17%. Customer Web Portal A total of 71 (53%) Smart Water Meter trial participants accessed the customer web portal during the trial period. Only 11 participants were identified as active portal users. An active user has been defined as a customer who logged on to the portal at least once a week for over 60% of the trial period. However, it is not known whether the customers logged on to the customer web portal to view their electricity or water use or both. Without this information it is difficult to conclusively assess what impact the ability to track and monitor water use has had on participant behaviour. The leak alarm was only provided through the customer web portal. Email or SMS alerts were not generated. KEY LEARNINGS AMI Integration Even though the AMI specifications for the SGSC were updated based on the learnings from the previous Newington Smart Village trial and lessons learnt extensively from other projects, the specification still needed to be tailored to the smart electricity metering system and smart grid. This demonstrates that every AMI system will require adjustments to the water meter specifications. The water utility needs to have a comprehensive understanding of their business rules and design requirements relating to the smart water meters and interfacing systems as there are currently no metering systems that will meet their needs fully. Understanding the consequences of their decisions on the system outcomes needs to be considered. There were a large number of integration/interface points in the SGSC communication network with multiple vendors which made it extremely complex to diagnose problems. As not all steps in the process were automated, it was time consuming and difficult at times to identify where the problem was in the SGSC system, preventing the meter data from being successfully transferred to Sydney Water. Product immaturity and interoperability with the smart water meter and the MMS presented challenges in delivering an integrated product solution. Technology Multiple Companies The complexity of the trial resulted in multiple companies products to deliver the end-to-end solution, which challenged Sydney Water s meter

specifications and functionality and created additional work to identify and assess options for minimising loss of water meter functionality expected for the trial. Testing The smart water meter communication with the AMI system was not completely stable during testing due to various reasons. This was reflected in the field which resulted in the water meter going off-line and loss of meter data. This highlighted the importance of field testing to validate the design in a live environment and any final adjustments to the firmware. Once in the field, problems were difficult to diagnose and capture which highlights the importance of laboratory testing to resolve all interoperability issues. Zigbee Even though the smart water meter and smart electricity meter were both independently certified to ZigBee SEP 1.1 and operating well in their own AMI systems, there was still extensive work required to integrate and stabilise the communication between Elster/Freestyle ZigBee and Ausgrid s AMI system. The smart water meter had an intermittent problem with the ZigBee service discovery process (meter s request to join the AMI system and exchange its ZigBee cluster and attributes settings with the electricity meter ESI) which resulted in a labour intensive process of commissioning the meters in the field and when water meters went offline. This feature should be enabled to eliminate the manual process of connecting the water meter to the MMS. Further work is required with the water meter before it meets all of its ZigBee SEP 1.1 obligations and inter-operates totally with the ESI/ZigBee Coordinator with respect to service discovery. The degree to which the smart water meter and electricity meter radio performance (using 2.4GHz frequency) is impacted is unpredictable. Therefore field testing is mandatory to assess the true performance of the radio and resilience to other radio interference. Sydney Water s current experience has shown the 433MHz frequency for radio communications to be more suitable for outdoor use as opposed to 2.4GHz. The 2.4GHz radio seemed to struggle in the dense tree areas and where there was no line-of-sight between the water and electricity meter. The ZigBee internal aerial in the electricity meter reduced the radio range under these conditions. Water Meter Alarms The handling of the water meter alarms needs to be managed appropriately by the AMI metering system. In this trial, PolicyNet could not manage the alarms to Sydney Water s requirements which resulted in confusion when the leak alarm (for example) was compared to the consumption data, since updates to PolicyNet were only sent when the alarm was triggered ON and not sent when the alarm was turned OFF. It is important that the AMI system transfers the meter alarms as they are updated. Water Meter Battery A small number (4%) of meters that drained the battery flat did not generate a battery alarm, which highlights the challenge of estimating the remaining battery life. The smart water meter s fully potted electronic register and battery (required to meet the IP68 rating) made it difficult to troubleshoot and resolve any problems with the meter s electronics or firmware if the battery is depleted. Water meter manufacturers should consider an alternative potting (sealing) material. Customers Recruitment The recruitment phase needs to begin well in advance of the meter installation as it takes a considerable amount of time and effort to recruit the desired customers. To ensure that the target number of customers is reached, more than double the amount of customers should be approached. This will allow for those customers that may be unsuitable or need to be excluded from the trial for various reasons. It cannot be assumed that once a customer is given a product, even if it is free that they are likely to use it. This was evidenced by the 47% of participants in the Smart Water Meter trial who did not access the customer web portal. If the tools to help customers understand and better manage their water use are not reliable or accurate then customers are less likely to continue to use them. This was shown by the very small number (11) of trial participants who were considered active customer web portal users. Data Management Hydstra database The existing Sydney Water Hydstra database that was used to store the meter reading and alarm data had limited capability in terms of analysing the meter data performance. As a result, the data had to be exported to an excel spreadsheet to complete the data analysis and produce the required graphs. Full consideration needs to be given in the initial stages regarding the database and analytical software packages selected to ensure that data collection and analysis are met. Data Transmission Reliability The electricity data proved to be useful when trying to diagnose the water meter transmission problems. Since the water meter was dependent on the electricity performance, it allowed Sydney Water to separate the WiMax from the ZigBee performance, although the MMS issues were difficult to separate and there was lack of diagnostic information. Ideally, the AMI system should provide a

breakdown of which part of the system is actually not working, so that the water meter can be managed correctly if no meter data is received. Properties that were fitted with two smart water meters (drinking and recycled) and were within eight metres of the electricity meter provided a good opportunity to assess the communication performance with the AMI system by minimising the distance as a contributing factor. Under this arrangement, the transmission performance for both water meters still varied, which highlights that the interoperability between the water meter and AMI system had not been optimised. Missing hourly water meter data created problems with the customer web portal by generating graphs with no data or large gaps. Customers have an expectation that their water use will be available when they access the portal. If this expectation is not met then customers may stop using the portal. Missing data also made data analysis difficult when attempting to identify properties with constant or intermittent leaks. Caution should be taken when assessing hourly data that includes gaps or interpolated values as it masks the actual water usage measured by the water meter, which can lead to wrong interpretations and conclusions. Water Use Data Sydney Water s quarterly drinking and recycled water consumption data was used to compare water use by Smart Water Meter trial participants against the water use of similar properties not involved in the trial. Using this approach improves the accuracy of the water savings estimates as it removes the impact of other non-trial related influences on water use such as weather and other general trends that occur throughout the population. However, the accuracy and ability to interpret the results from this analysis is limited due to the insufficient length of the trial and the small sample size of participants which does not enable robust statistical analysis to be completed. These limitations need to be considered when using the analysis results. It is recommended that any future trials should be designed to enable valid statistical analysis to ensure robust results and that the trial be conducted over a period of at least a year. Resourcing as the consent forms, letters and frequently asked questions, and approval from the trial partners and the Federal Government was quite time consuming. The pre-installation, installation and commissioning processes were the most resource intensive. These stages required multiple Sydney Water and Ausgrid teams to be in the field and the back office simultaneously. Future automation of the commissioning process would minimise the resources required. The resourcing requirements of such a trial should not be underestimated and need to be given sufficient consideration. CONCLUSION The SGSC trial presented an ideal opportunity for Sydney Water to test the efficacy of integrating smart water meters into an electricity smart grid system. In theory, the benefits of utilising the communications infrastructure that already exists for the electricity smart grid by linking the water meter to the electricity meter appear obvious. However, the trial has clearly shown that there are significant issues around the electricity and water meter wireless communications technology and interfaces with other systems that need to be managed for this arrangement to be effective. The Smart Water Meter trial demonstrated that while it is possible to run a joint AMI, product immaturity and interoperability of the smart water meter and Ausgrid s AMI, presented challenges in delivering an integrated product solution that will meet all of our water requirements. The commercial aspects were not analysed but would be problematic at many levels. NEXT STEPS At this point, the costs of smart metering significantly outweigh the benefits for Sydney Water. The technical aspects of smart metering are understood and cost estimates are reasonbly accurate. However, the technical challenges still need to be addressed and the benefits need to be better understood and quantified. Sydney Water will keep a watching brief on smart metering and intelligent networks in Australia and internationally, and continue to share any findings to inform the water industry s position on any future roll-out. A significant level of resourcing was required throughout the Smart Water Meter trial and involved numerous teams within Sydney Water. While Sydney Water did not directly recruit the customers for the Smart Water Meter trial (organised by Ausgrid), a high level of resourcing was required during the recruitment stage in terms of determining the suitable properties in the back office. Preparation of the customer collateral such

Figure 1: Electricity Smart Grid Smart City AMI

Figure 2: Customer web portal