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Trends in DWTP management for 2021: centralized, autonomous control

  • Trends in DWTP management for 2021: centralized, autonomous control

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In 2021, progress will be made towards a centralized, totally autonomous control over drinking water treatment plants, transcending silo-based process management. Miren Aldecoa, Water Treatment & Desalination Consultant at Idrica, identifies in this article the key trends in DWTP management for 2021.

The present and the future of DWTPs

The new trends in DWTP management aim to solve a common problem in drinking water treatment plants (DWTPs), namely process fragmentation, stemming from the use of different technologies and operating modes. The updating and interconnection of the different SCADAs, which usually emerge ad hoc with each revamping, expansion or new process, is a challenge for the team and makes it difficult to optimize the DWTP.

As a result, and given the importance of these facilities for the supply of drinking water in terms of quantity and quality, these plants tend to rely on significant human resources for their operations.

This is mainly due to the lack of tools and equipment to collect sufficient information and perform the tasks at hand. However, automation is increasingly gaining ground in daily operations, overcoming the initial reluctance and investment constraints.

Trends in DWTP management for 2021

1 - Advanced predictive control of DWTPs

There are several steps on the way to full plant automation. Basic automation, which is already common in several countries, collects information through instrumentation for subsequent manual control. In this sense, PID control is a clear improvement over previous methods, as it enables a proportional, integral, derivative reaction to errors. For example, the required amount of chlorine can be adjusted according to the data collected by the analyzer.

The next step, advanced predictive control, is the latest trend. This system automatically adjusts the predictive model parameters to the cause-effect relationship of the process and its variations over time. The algorithm learns and calculates the ideal level of each parameter, so that their adjustments no longer rely on human decision-making. At present, this type of control is being implemented on a pilot basis for some cases of use, but the trend is for it to be mainstreamed into overall plant management.

The cases of use in which advanced predictive control is applied, for example, involve predicting the quality of the water collected, automating dosing for coagulation, simulating the properties of the chemicals stored, monitoring decanters, optimizing filtration and pumping, monitoring water as a product and calculating microbiological risks.

For this transformation to work, people need to trust in automation as the best way to eliminate unintentional human error, and as a more reliable option than manual measuring.

2 - Integration and analysis of all relevant data

To achieve stand-alone control of an entire plant, all the data that may have an impact on its operation must be integrated. This includes, for example, external data such as weather forecasts. Sometimes, this process will temporarily involve entering manually collected data into the system, until the appropriate tools can be implemented.

The integration of all the information in a single platform ensures that everything is in place to make decisions and predict processes automatically, with recommendations for action being issued where appropriate. For example, if a storm is expected in the next 24 hours, operators are alerted so they can adjust the coagulant dosage before the turbidity changes.

It will then be up to the operator to decide what to do with these operating strategies, running them manually or automating their solution. Advances in mechanical, hybrid and AI methods are behind this new approach to plant management, which is essential for the smooth running of processes.

The water industry expects the technological solutions that group information together and issue subsequent recommendations to be modular, agnostic, interconnected and scalable so they can be customized to cater for the reality of each individual plant - and sometimes to the reality of more than one.

3 - Asset life optimization

In line with a move towards greater sustainability, the trend is for predictions - rather than manufacturer recommendations - to outline the best time to replace an asset or update its maintenance schedule. In addition, new technological solutions will enable corrective actions to be taken when necessary, performing predictive, proactive maintenance, since the system will detect trends and make specific recommendations to operators, in order to extend asset life.

4 - Detection of possible threats

In the future, we will see how systems increasingly take into account the detection of possible threats to the population through drinking water. The monitoring of variables will serve to avoid crises based on viruses and bacteria (SARS-CoV-2, Legionnaire's disease, etc.), as well as any other event that could affect water security.

Idrica's Global Water Trends 2021 report provides a comprehensive list of trends for the industry, including the trends in DWTP management for 2021.

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