Utility Week - authoritative, impartial and essential reading for senior people within utilities, regulators and government
Issue link: https://fhpublishing.uberflip.com/i/201852
Operations & Assets Market view Market view Smart on leakage Simulate, stimulate Rob De Nijs argues that smart water meters could do wonders to help water companies detect leaks. W ater leakage is an economic and environmental problem. In England and Wales, the average family uses 500 litres of water every day – 50 per cent higher than 25 years ago. Moreover, the use of water in homes produces 35 million tonnes of greenhouse gases a year – approximately 1kg of carbon per person per day. Water companies are now starting to see financial benefits in reducing non-revenue water (NRW). On average, NRW rates are around 21 per cent, with leakage making up a significant proportion of this total. The costs of treating, pumping and distributing water make water companies some of the biggest energy users in the commercial sector, consuming 3 per cent of the total energy used in the UK. Consequently, money and time spent on water that is subsequently lost is money and time wasted. One of the most effective ways to monitor and reduce water leakage is by installing smart meters, which use big data to inform water companies of precise flow rates and any discrepancies that might indicate a leak. Three types of solution are available. The first is metered leak detection. At the very end of the network, in or around the consumer premises, it is possible to identify lots of small leaks that permanently waste water, which neither the consumer or utility is aware of. Installing a meter is the first step, because only what can be measured can be managed. The capabilities of the meter will depend on the solution deployed but most will be able to flag abnormal consumption such as a permanent leak to the utility, which in turn can notify the consumer. The second type of solution is a district meter network. Real losses in water networks can be the main contributor to NRW and addressing these through district meter networks can present significant savings. The process works through a few simple steps. First, install a meter in a location that feeds a particular area or district, this becomes the master meter. Second, identify all the premises this master meter feeds and meter these individual accounts. Aggregating their total consumption will present the utility with the 24 | 1st - 7th November 2013 | UTILITY WEEK total input and total output of this particular network. Comparing the net consumption of the master meter and that of the district will identify any discrepancies. A sometimes overlooked area of meter networks is that of apparent losses. One of the hardest parts in managing a traditional water meter network is that most of the time, meter ageing or damage is not detectable. Older meters that have been installed can be tampered with or lose their accuracy, often unbeknownst to utilities and consumers. Newer, more advanced meters can detect abnormal meter behaviour and send a message back to the utility informing them of tamper or measuring inaccuracies. The third solution is acoustic leakage detection. A dynamic combination of acoustic leak sensors, advanced metering infrastructure technology and data analysis software enables proactive leak mitigation. Using a communication module with an integrated acoustic leak sensor, water companies can collect and analyse vibration patterns from anywhere in the distribution system, significantly improving their ability to proactively maintain critical water infrastructure. Leakage reduction is imposed on utilities using the sustainable economic level of leakage (Sell) framework. Although Sell can limit the amount of capital utilities dedicate to reducing leakage, a structured approach is of paramount importance. From a cost-benefit analysis, implementing smart water metering projects should not be viewed solely as a way to cut leakage. Smart metering has many benefits, from accurate billing and customer service improvements to network efficiencies and improved demand forecasting. Leakage reduction is an additional benefit. Smart metering infrastructure upgrades can be a costly procedure, but the benefits are far reaching and returns can be immediate. Once implemented, they provide actionable data that utilities can use to tighten their focus on conservation and create a sustainable future for their customers and their business. Rob De Nijs, solutions delivery manager, Itron Meter data simulation will be the first smart move, says Mark Thompson. S mart metering technologies are now either being deployed or are on the brink of deployment in many countries, but in many cases there is still a lot of uncertainty about the effects that their introduction will have for network operators, suppliers and customers. We all know that smart meters will enable remote operations and generate enormous amounts of data, and that they should deliver a wide range of benefits if the necessary improvements to business processes, information access and IT systems can be made. Energy companies know they will face real challenges, but they have lacked the tools to technically assess the impact of smart metering on downstream systems and processes. Meter data simulators have the potential to change this situation completely. A simulator works by creating a logical model of the low-voltage distribution network, from the grid down to the substations and phases – and smart meters that have been connected. The simulated model can then be used to generate dummy meter data and mimic the live operations of the metera to simulate a range of scenarios. In its work on simulation so far, AMTSybex is focusing on modelling different types of power outage. These outages are a major pain-point in the energy sector. Network operators are penalised for failing to maintain a secure supply, while energy suppliers will face a flurry of customer complaints and information requests until the fault is fixed. Working with one of our distribution network operator clients, we are developing a solution that will be able to simulate a wide range of outage scenarios and understand how meter data can help the network to respond more quickly and effectively. For example, we can model a situation where an electrical fault causes one or more of the feeders at a substation to go offline. The customers whose meters are connected to the affected feeders lose power, but before they do so, we simulate the meters sending a last gasp message to the central database,