Digital transformation of wastewater treatment plants. Why data becomes crucial

In response to technological and civilization challenges, the water and sewage industry is starting to move from a reactive to a predictive model, reaching for advanced analytics. A key role here is played by solutions using the so-called digital twins, i.e. virtual models of real objects or processes that operate in parallel to them and reproduce their behavior in real time.

The water and wastewater industry is at a turning point

Until recently, the management of sewage treatment plants was based largely on the experience of operators, laboratory analyzes and responding to current events. This model, effective for years, is now increasingly no longer relevant to the realities of the industry. Rising energy costs, tightening environmental standards and the increasing complexity of technological processes mean that the water and wastewater industry is at a turning point.

Modern wastewater treatment installations are multidimensional systems in which biological, chemical and mechanical processes interact in real time. As noted by Dr. Eng. Bogusław Buczak, director of the Process Engineering Department at SEEN Technologie Sp. z o. o., the number of variables influencing the final technological effect is so large today that their effective control without the support of advanced tools becomes practically impossible. In such conditions, the traditional approach, based on point measurements and analyzes performed with a delay, is no longer sufficient.

The consequences are very specific. High energy consumption – especially in aeration processes, excessive dosing of chemicals and increased risk of technological disruptions translate directly into operating costs and stability of the installation. As a result, the sewage treatment plant increasingly ceases to be a predictable element of infrastructure and begins to function in a mode of continuous response to changing conditions.

From reaction to prediction: a new management paradigm

It is this change in scale and complexity that is causing the industry to shift towards data-driven solutions and automation. However, this is not just a matter of technological ambition, but rather a necessity. In a reactive model, it is increasingly difficult to achieve repeatable, optimized results. Therefore, the importance of a predictive approach is growing, in which the key is not so much reacting to disruptions, but anticipating them and preventing them before they occur.

– Without automation and real-time data analysis, we are unable to obtain stable, optimal results – points out Dr. Karol Trojanowicz, technologist at SEEN Technologie Sp. z o. o. He adds that modern systems not only support operators, but in practice enable the process to be conducted at a level unavailable using traditional methods.

A natural consequence of this change is the growing importance of digital process models. One of the key tools is the so-called digital twin – a dynamic mathematical model that reproduces the actual installation and all processes occurring in it. Unlike classic control systems that respond to the current state, this model allows you to simulate various operating scenarios and assess their effects before making changes to the actual system.

In this context, solutions such as ASOS® (Automatic Supervision & Optimization Service) appear – systems that combine data from online sensors, process algorithms and mathematical models into one coherent ecosystem. Their role is not limited to controlling the installation: in practice, they act as a digital technological advisor, analyzing many variables at the same time and recommending the most effective operating strategies. At the same time, thanks to data centralization, control over information flow and standardization of control logic, systems of this type constitute an important element of the cybersecurity architecture of modern sewage treatment plants, limiting the risk of unauthorized interference and increasing the infrastructure’s resistance to digital threats.

As experts point out, the key change is the transition from making decisions “based on experience” to decisions based on multidimensional data analysis. The operator no longer has to independently interpret measurement results and predict the effects of his actions – the system performs these operations continuously, providing ready-made, optimized process settings. – This is not a classic control system, but an advisory system that allows for comprehensive optimization of the entire process – notes Bogusław Buczak. He adds that in practice this means the possibility of maximizing the potential of existing technology.

Efficiency, stability and ESG – three pillars of change

The dimension of this transformation is best seen in specific operational effects. In the most energy-intensive processes, such as aeration of activated sludge chambers, appropriate optimization can lead to a reduction in energy consumption by up to 20-30 percent, which in large installations means savings of hundreds of megawatt hours per year. At the same time, it is possible to significantly reduce the consumption of chemicals while maintaining the required quality of treated sewage.

An important effect is also the stabilization of the operation of the entire technological system, including anaerobic processes responsible for biogas production. In practice, this translates not only into greater installation reliability, but also into improved energy balance of the plant and its overall profitability. Importantly, thanks to the use of advanced analytical systems and process models, it is possible to have a real impact on the way the process is conducted, including its intensification, which directly affects the increase in biogas production. This also opens the way to obtaining additional economic benefits, such as the possibility of obtaining the so-called white certificates, and also increases the energy independence of sewage treatment plants from fluctuations in the prices of energy carriers, including crude oil.

Digital transformation in the water and wastewater industry is part of a broader trend related to the development of Industry 4.0. Wastewater treatment plants are no longer a set of separate devices controlled locally, but become integrated systems in which data flows between sensors, control systems and analytical models. ASOS® is an example of this approach, combining the physical layer of infrastructure with its digital representation and enabling two-way exchange of information between them.

One of the most noticeable effects of this change is the increased stability of the installation. The ability to predict events – from fluctuations in pollutant load to potential process disruptions – allows you to reduce the risk of failure and better plan the operation of the treatment plant. In practice, this means a transition from crisis management to anticipatory management.

The environmental aspect is also important. Optimizing the consumption of energy and chemicals translates directly into reducing the carbon and water footprint, which is in line with the sustainable development goals and ESG reporting requirements. At the same time, maintaining a stable quality of treated sewage, regardless of changing operating conditions, becomes easier to achieve.

Algorithms are as important as physical infrastructure

Everything indicates that the water and wastewater industry is entering a stage where data and algorithms become as important as physical infrastructure. The sewage treatment plant ceases to be just a technological installation and begins to function as a decision-making system, capable of continuous learning and adaptation.

Solutions such as ASOS® are therefore not just another technological tool, but an element of a broader change in the way of thinking about process management. In this sense, the transformation we are observing does not only concern individual plants, but the entire sector and strongly affects its role in the economy, energy and environmental protection.