Optimising performance across the water cycle – by harnessing data to predict and act

Water companies in the UK are facing new legislation to deal with the sewage discharge problem, plus continued regulatory pressure on leaks and water quality. But tech solutions, such as virtual modelling via a ‘digital twin’, are bringing results to water companies in Germany, Sweden and the UK, as Andrew Welsh, sales director for global water technology company Xylem reports.

With just 14% of the UK’s rivers rated as good by the Environment Agency, pressure is growing on water companies to address – as a priority – the discharge of raw sewage directly into watercourses.

None of England’s rivers meet quality tests for pollution, according to statistics from the Environment Agency. The Department for Environment, Food and Rural Affairs (DEFRA) took the step of setting up a taskforce in September 2020 to cut the frequency of sewage discharges into rivers and seas, as well as from storm overflows. This followed revelations that water companies had released raw sewage into rivers more than 200,000 times in 2019.

Consequently, earlier this year, environment minister Rebecca Pow pledged to bring in new legislation to tackle the increasingly poor state of rivers and to cut dumping by water utilities by September 2022.

It is no surprise that the news has caused ripples among the UK’s water utilities. Minimising environmental impact is an ongoing challenge for the industry, where key sources of pollution are raw sewage discharges directly into rivers, chemical discharges from industry, and agricultural run-off.

So, what are the solutions to offer tighter controls, to reduce combined sewer overflows spills and to cut internal and external sewer flooding?

Modelling performance to improve effluent quality
With energy efficiency and forward flow optimisation among the key considerations for wastewater treatment, additional instrumentation holds the key to data-driven decision-making that can reduce operating costs by boosting performance. This was the aim of German utility company EWE Wasser, which applied a “decision intelligence” approach to its north German Cuxhaven Wastewater Treatment Plant.

EWE used a real-time digital twin of the entire plant, which sits on the North Sea at the mouth of the River Elbe, including the development of virtual sensors to calculate an estimate of the incoming carbon, nitrogen, and phosphorous loads of the influent.

By modelling performance in a computer environment, they were able to optimise plant operation and improve effluent water quality. The concentration of nitrogen in the treated water met, and continued to maintain, regulatory standards – an even bigger win for the utility than the 26% reduction in aeration energy usage also achieved.

Layering equipment with technology for wastewater networks Concentrated sludge build-up and clogging can hamper performance in wastewater networks and lead to increased wear and tear, limiting the lifecycle of assets as well as lowering the transfer of water. All bad news for utilities aiming to improve energy usage and reduce costs amid the maintenance challenges of an ageing infrastructure.

By adopting equipment that can adapt to its environment, reducing downtime and offering new levels of performance with self-cleaning impellers to lower energy use and reduce unplanned maintenance costs, an optimised performance is achieved.

The addition of integrated intelligence – which senses its environment and adjusts its processes accordingly – drastically reduces unplanned downtime. This type of total pumping system senses the operating conditions and adapts its performance in real time to deliver optimal functioning and reduce service callouts.

Preparing for tighter parameters on clean water
With effluent quality as an area of growing focus, and faced with a growing list of pathogens and contaminants of note, optimising biological treatment is seeing the development of computational fluid dynamic (CFD) modelling to predict flow fields and hydraulic behaviour.

This was used in the Swedish city of Gothenburg, the country’s second largest city, to supply water from two drinking water plants to the city’s 500,000 inhabitants. A validated ultraviolet (UV) solution was required that would fit and operate in a 62-year-old plant which had not been originally built to facilitate such technology.

A model of the UV reactor and final piping arrangement provided performance data under real-life conditions prior to the unit’s actual installation and operation. When installed, this additional stage of UV protection against microorganisms offered a sustainable, chemical-free solution, as well as the lowest lifecycle costs.

Taking proactive steps to manage leaks
Improving metering technology offers a path to a more affordable and sustainable water supply to address a UK landscape indicating as many as four in ten households having small water leakages at any given time.

When a residential customer does have a leak, 40% of consumption happens at low flow. Real-time monitoring via low-flow residential meters is an optimal, low-maintenance option for utilities without any mechanical parts that have the potential to clog. As well as detecting water leakage, this also improves accuracy of billing to residents, improving customer servicing.

Data-driven insights achieved by monitoring and analysing operations can allow utilities to optimise performance to minimise wear and tear, reduce cost, and minimise their environmental footprint.

A successful pilot with Yorkshire Water in Hadfield has delivered the installation of a smart network that offers remote and continuous monitoring of operations – allowing real-time reactive management and maintenance. The project uses data from thousands of smart digital meters as well as temperature, pressure, and water quality sensors to revolutionise the approach to leak management and supply interruption reduction. Thanks to the data available, proactive decisions can be taken and pre-emptive adjustments made to prevent issues before they happen.

Moving beyond predictive maintenance
Successful outcomes rely not only on adopting the smartest mechanical equipment available but in understanding how they can be adapted to minimise downtime, reduce wear and tear and save on energy usage and maintenance costs.

Remote monitoring and data acquisition technologies enabling utility managers to keep an eye on their assets in real time, even when not on site, is another positive outcome where manpower is stretched, as was the pressure on operations experienced during the Covid pandemic. By providing advanced instrumentation for multiple sensor networks, parameters could be measured throughout an entire process, such as a wastewater treatment plant, with one system.

As utilities seek tighter controls in order to minimise combined sewer overflows spills and reduce their environmental impact, improving performance across the water cycle relies on two elements: top-performing mechanical equipment, coupled with digital devices and AI that deliver powerful insights. In turn, this can drive knowledge-based decisions and help the industry move away from a reactive maintenance plan to a smarter approach that offers the power to sense, predict and act.

Gathering and integrating data, from sensors and software systems, then channelling it via machine learning can allow utilities to predict how each system will work in any given scenario, establishing the best processes for the correct outcome along the way and lessening the chances for unexpected spills and overflows.

These predictive insights allow utilities to identify and access potential problems before they occur and are equally available from legacy data sources and existing fixed monitoring instrumentation. Taking a proactive stance thus enables water managers to exploit the data available to them, reduce system losses and actively manage assets – to achieve optimal performance and avoid unexpected and costly sewage discharges, both to the water company and to the environment.