Efficiently detect and reduce water leakage with AI

Wasting water just feels wrong for Swedish water company VA SYD. So its engineers developed a smart leakage detection system that helps protect as much of the valuable resource as possible. It enables to efficiently detect and reduce even the smallest leaks on water pipes thanks to the support of artificial intelligence (AI) from Siemens.

Swedish water supplier VA SYD provides customers in Malmö and Lund with drinking water
Based in Malmö, Swedish water supplier VA SYD operates a total of around 5,000 kilometers of pipelines, 2,000 kilometers of which are for drinking water.

“Treating natural resources with respect is a way of life in Sweden, and water use should be no exception to this practice,” says Victor Pelin. “Plus, lifting, treating, and pressurizing that water consumes energy, and energy is a major cost factor,” adds Simon Granath.

Simon Granath and Victor Pelin work as development engineers at VA SYD and have been responsible for the design and implementation of the leakage detection system. Their goal: to reduce the 10 percent of wasted water due to leaks, so-called non-revenue water, to less than 8 percent. This contributes to VA SYD’s ambitious goal of becoming a climate-neutral, energy-positive water utility by 2030.

Pinpointing leaks is a complex task. “Until very recently, we could detect only the largest leaks that led to service disruptions.  In fact, it is the smaller, slower leaks, often from small service pipes, that are responsible for the lion’s share of non-revenue water,” Simon Granath points out. That just wasn’t good enough for the most precious resource of our planet.

Improved customer service

Another aspect is improving service to customers. “We have to maintain a lot of pipelines in a large area, and we wanted to improve our ability to pinpoint leaks through smart metering zones. For this purpose, we set out to find an AI-based solution,” Victor Pelin recalls.

VA SYD evaluated several systems over the last few years, looking for a solution that was state of the art. It would also have to make optimum use of the available flowmeters and smart meters in the area that had been chosen for the proof of concept. SIWA LeakPlus ticked all the boxes.

Collaboration leads to an optimal AI solution

“But when it came to the implementation concept, we ran into some obstacles. We had to find a way of using the AI-based leakage detection in an on-premises set-up instead of a cloud environment. We then had some in-depth discussions with Siemens, their cooperation partner BuntPlanet, and our IT and OT departments about the best approach to install the SIWA LeakPlus solution in our own data centers. To my knowledge, this is the first time something like this has been done in the Swedish water industry – and we managed to get the job done,” says Victor Pelin. Simon Granath adds: “We want to be able to measure up to the best. That requires AI-based solutions like SIWA LeakPlus.”

Simulation approach for improved data

The next step was to refine the hydraulic models for the pipelines and link the data from the metering systems and pump stations with SIWA LeakPlus using OPC UA. VA SYD was then ready to perform the first tests. Victor Pelin explains: “We used the system to simulate different leaks and then evaluated the data. We were able to detect leaks as small as 0.5 liters per second – a huge improvement over the previous solution, which provided no means of detecting small leaks at all.”

SIWA LeakPlus

SIWA LeakPlus is one of the Siemens Water (SIWA) applications specifically developed for the water and wastewater industry. This smart solution uses an AI-based algorithm to identify and classify anomalies in the pipe network. To perform reliably, SIWA LeakPlus is first “trained” with historical flow and pressure data so that it learns to separate anomalies from regular operation and assign the correct cause to each anomaly.

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“In the coming weeks, we will introduce a further developed variant of leak detection, which will allow us to determine the exact location of the leak. Then we will have the means to really go out there and fix all those small issues efficiently,” Simon Granath says.

Savings speak for the solution

With the proof of concept in its final stages, Simon Granath and Victor Pelin are also working on scaling up the solution to other parts of the network. The next area to benefit from SIWA LeakPlus will be the town of Lund, where
VA SYD is currently installing additional flowmeters to provide more data from the pipeline network. “A smarter leakage detection system requires less data from the pipelines, so we can reduce the number of installed meters. This immediately pays off,” Simon Granath is convinced.

Economic benefits aside, SIWA LeakPlus has already helped VA SYD take the next steps toward another ambitious goal: by 2030 the company wants to become a climate-neutral, energy-saving water utility with zero unplanned service disruptions.


Original post: https://www.siemens.com/global/en/company/stories/industry/2021/va-syd-water-artificial-intelligence-ai-cloud-sweden.html

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