As the stewards of that lifeblood resource, water utilities are facing increasing challenges as they strive for greater efficiency in their operations and to be socially, economically and environmentally sustainable.
Across the water lifecycle from source to tap as clean and safe drinking water and back to the environment via waste, water suppliers’ processes are energy intensive and costly. And with much of their infrastructure ageing and underground, unseen leaks are one of their greatest losses.
So how can these challenges be addressed, before there is a major disaster such as a flooding caused by a leaking water main?
“I always say that no news is good news for a water utility,” says Gary Wong, Global Water Industry Principal at OSIsoft, in an interview with Engerati. He cites the example of the Water Corporation of Western Australia, which claims to save Au$1m (US$0.8m) in lost reputation by avoiding front page newspaper events.
“It’s all about data and turning it into actionable information – without their data, utilities are flying blind and drawing on their past experiences.”
And there can never be too much data, he adds – “but it’s got to be managed efficiently and effectively with a big data strategy.”
Water industry data challenge
As their electric counterparts have experienced in the context of the smart grid, the same new distributed technologies such as sensors are opening the way for deeper real-time management of smart water distribution networks.
“With the emergence of the internet of things (IoT) we are seeing technology costs dropping, advanced sensors bringing analytics to the edge, and interoperability out of the box, all reducing the barriers to entry and enhancing the ease of deployment,” says Wong.
Parameters such as water pH, turbidity, pressure and flow rate via sensors should become basics for the water industry, alongside the standard meter data and other reads such as power usage, he continues.
But data isn’t just about operations. A big data strategy must integrate the operational technology (OT) with the back-office information technology (IT) such as the financial and asset management systems to maximise the value across the utility.
“For example, one can learn a lot from adding geospatial information to the OT data. Water pipes are widely distributed and plotting them on maps with the OT parameters could provide an early alert to a problem such as a leak.”
With such a strategy Vitens in the Netherlands is able to detect a leak within 2 minutes.
Another example of an OT-IT integration is the opportunity to move to a condition-based asset management programme. Using run-time hours to drive maintenance instead of an age-related schedule, San Francisco Public Utilities Commission’s Wastewater Enterprise expects to save $1.7m/year.
Then there is also social media, which must be factored into a big data strategy, especially for customer communication.
“How much better for the utility to notify customers there is a leak with the goodwill that creates than for the customers to be notifying the utility.”
Water industry data strategy
Wong advises that when considering a big data strategy, the water utility shouldn’t look upon it only as a cost but as an investment with returns, both to support that investment and to encourage a more proactive approach.
He indicates that the strategy should be based on ‘best of breed’ software, which can be implemented rapidly and without the need for customisation and is scalable and secure.
He also advises against one-off type applications, which effectively don’t amount to a strategy and may not offer full interoperability.
Potentially the biggest challenge is going to be internal within the utility as the OT and IT data – and the respective personnel – is likely to be ‘siloed’ and needs to be integrated through a single system.
“This is why a long-term big data strategy is needed,” says Wong. “All the data is important but it is the combination of the OT and IT spaces that enables ease of access to the data and gives it context.”
He adds that whether the analytics is located centrally or at the edge is not critical – nor whether it is done in-house or in the cloud.
“Location doesn’t change the data management requirements and the same issues come into play. Ultimately it’s about utilities having ‘one source of the truth’ that they can use to provide actionable information.”
Water utility business value
The water industry still has some way to go to catch up with their electric counterparts in terms of water data management.
For example, in North America over half of the water utilities don’t have a big data strategy and nearly 60% don’t mine their existing data to better understand their customers or processes, according to the American Water Works Association’s 2015 State of the Water Industry report.
But those that are pursuing such strategies are demonstrating real value, as the examples quoted above and others show.
Among other utilities with which OSIsoft has worked, which Wong quotes, Veolia Eau in France has reduced energy costs by 6% and improved leak detection by 7%.
In Canada, Halifax Water has reduced water leakage by 40Ml/day, saving C$600,000 (US$445,000) annually, while in UK Yorkshire Water realised nearly £1m in energy savings within 12 months.
Some utilities also are developing innovative new applications, such as United Utilities in the UK, which is using artificial neural network modelling to forecast demand from 24 hours to a week ahead.
“Each utility has its own strategic requirements for the data it gathers but we believe that with the emergence of the IoT and more sharing of data, water utilities, like the electric utilities with electricity, will move to monitoring every drop of water and where it’s come from and who’s using it,” Wong says.
“Saudi Aramco monitors every drop of its oil and indeed some utilities, such as Veolia Water, are already moving towards full traceability of water. That is the value that data can provide.”