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What are Intelligent Wastewater Networks? How do they contribute to the REWAISE project?

12 June 2024

Dr Sonja Ostojin headshot

Dr Sonja Ostojin

Head of Innovation

EMS
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River

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 869496

The REWAISE project, or the Resilient Water Innovation Economy project, is about action to move towards a carbon-neutral water cycle. This will factor in technological, financial, legal, and social issues to better manage our water cycle, in the face of population growth and climate impacts. In practice this means delivering a carbon-free, sustainable hydrological cycle in line with the concept of a resilient circular economy. (Rewaise.eu)

Intelligent Wastewater Networks are vital to the success of these aims, and involve the use of sensors, data collection, analysis and real-time control in wastewater networks.

In this article Prof Pete Skipworth and Dr Sonja Ostojin examine Intelligent Wastewater Networks and the role of technology such as EMS’s CENTAUR. Here they discuss how it assists in solving the problem of excessive CSO spills, contributing to the above aims.

Why does the UK struggle with CSOs?

100,000 kilometres of England’s sewer pipes were built before the mid-1960s and carry two kinds of wastewater: rainwater from street drains and sewage from homes. As these combined sewers were built many decades before modern rates of population growth and accelerating climate impacts, there is often now more sewage and rainwater going into these systems than first expected. (water.org)

The effects of climate change, population growth and urbanisation are putting increasing pressure on sewer and drainage networks, both in the UK and overseas. The capacity of networks to cope with surface water runoff often falls short of requirements, leading to localised floods and/or increased CSO spills to receiving waters. Climate change is, for example, resulting in more intense storms in the UK. Equally, increased urbanisation means increased volumes of runoff must be conveyed by the same downstream infrastructure to wastewater treatment works. The response to these pressures has often been capital solutions such as storage tanks, or increased sewer size. These solutions are disruptive and have large associated costs and embedded CO2, for example from the use of concrete.

Smart water or wastewater network technologies have the potential to deliver improved service to customers, cost-effective performance improvements and lower CO2 emissions for the water industry.

CSOs and public concern

The UK government’s Storm Overflows Task Force reported that CSOs in England spilled over 340,000 times in 2020. Publication of this data resulted in public concern, which led to new obligations for Water and Sewerage Companies within the Environment Act 2021. A statutory Storm Overflow Discharge Reduction Plan (SODRP) sets stringent new targets to protect people and the environment.

This will require water companies to deliver the largest infrastructure programme in water company history.

By 2030, SODRP aims to eliminate spills from 3,000 storm overflows affecting the most sensitive rivers and reduce annual spill frequency to bathing waters to less than 2 per bathing season. For all other CSOs, of which there are an estimated 15,000, the goal is to eliminate 40% of spills by 2040 and 80% by 2050. The cost estimated for meeting the SODRP is £12-19Bn. This is to be the largest program to tackle CSO spills in the UK water sector’s history and will impact water bills. This estimated cost is based on constructing new in-system storage at CSOs, and widespread use of SuDS or disinfection technology. These are capex-, space- and carbon-intensive.

Real Time Control systems protect against uncertainties

Uncertainties related to the extent of future rainfall patterns, as well as large investment costs associated with extending urban drainage systems to maintain or improve performance levels, call for flexible and adaptable solutions to improve the operation of existing drainage infrastructure.

Real-time control (RTC) systems are designed to improve the operation and management of existing urban drainage assets. This is done by monitoring the state of the system and then regulating the flow conditions in real-time. RTC systems can be local control systems, or system-wide control systems. In local RTC systems, the control strategy usually relies on a limited number of actuators acting independently, and the operation is managed following direct measurement (e.g. level, flow) within the area impacted by the RTC system.

Local control can have the advantage of reduced effort and expense, and increased reliability, for data transfer compared with a complex network-wide RTC system. The operation of local RTC does not depend on wider communication with central RTC servers, or online models, enhancing the resilience to failure of the system. Local RTC is adaptable as it can be modified/extended by the addition or relocation of actuators without the alteration of pre-existing RTC infrastructure or control strategies, in response to network changes or possible future changes in climate.

What is CENTAUR?

CENTAUR is an intelligent autonomous system for reducing local escapes from networks, for urban flooding or CSO spill reduction. It utilises untapped network capacity via the operation of a gate to control flow based on an intelligent algorithm which uses local real-time water level data. CENTAUR is a self-managing, easily deployed system, which can be much less costly than capital, space- and CO2-intensive solutions such as storage tanks, enlarged sewers, or blue-green drainage systems.

The control intelligence for CENTAUR is a fuzzy logic algorithm. It could be said that the increased network handling capacity and financial benefits (capital avoided) come from the algorithm. However, without the robustness of monitoring and communication technologies as the enablers, the effective application of AI would not be possible.

The need to better understand and utilise AI in the UK water industry

There are some obvious dangers in the use of AI in that bad decisions can be made if left to operate autonomously, unchecked. However, this happens through the poor design and poorly considered application of AI. We can see from the successful application of CENTAUR that good design (hardware/software, including control algorithm) can avert such dangers.

Operators may be put off by the newness of artificial intelligence (AI) and be reluctant to take on technologies they don’t understand. For this reason, it may be a mistake to put the algorithm “front-of-house”. PCs and PLCs in everyday use in the water industry use many clever algorithms, but it isn’t necessary for the user to understand these, and they aren’t put front-of-house when their virtues are under review. Having said this, the human readability of fuzzy logic may be part of the reason why this type of AI is finding more traction in the water industry.

There have been many misuses of such arguments against automation to satisfy the human tendency to steer away from change, most notably the Luddite fallacy – the thinking that innovation would have negative effects on employment, causing technological unemployment. While there are significant economic advantages, it may be down to those in positions of power – company leaders and economic regulators – to make sure the potential of AI in the water industry isn’t ignored.The power of these technologies, if designed and applied properly, can have large operational and economic advantages which should not be overlooked.

General Adoption of AI

To realise the benefits of AI, we need to internalise the power in better products and more robust platforms which have been designed to guard against the downsides of AI. These downsides include the inability to communicate them effectively.

Developing a comprehensive framework to address the multifaceted social and organisational aspects that could impact AI adoption in companies is imperative to achieve successful outcomes. This framework should examine the decision-making processes surrounding AI adoption, examining criteria like cost, feasibility, and perceived benefits. Additionally, it must factor in employee attitudes towards AI, investigating concerns, fears, and perceptions of AI’s impact on their roles and workplace dynamics.  Unlocking the full potential of AI integration hinges on an understanding of the requisite knowledge and skills. It’s not just about technical proficiency; it’s about fostering ethical awareness and cultivating adaptability. The ultimate goal of such a framework is to formulate guidelines, tools, and recommendations that streamline human-AI collaboration, mitigate resistance, and foster a harmonious integration of AI technologies into organisational workflows. By addressing social and organisational factors, companies can ensure smoother transitions to using AI, maximise the potential benefits, and minimise potential drawbacks. This holistic approach not only enhances the efficiency and effectiveness of AI utilisation but also promotes a culture of innovation, continuous learning, and responsible AI deployment within organisations.

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