EFFICIENCY AT EVERY LEVEL: DIGITAL TWINS FOR DESALINATION

All over the world, people and businesses increasingly rely on desalination to meet their water needs. To keep up with this steadily growing demand, desalination plants need to be built faster and operate more efficiently.

Standardisation, automation, and digitalisation provide a whole range of solutions to increase the speed of engineering and designing such plants, as well as exploiting their full potential. Through the use of these tools, desalination plants can create value from data to streamline operations and maximise the efficiency of not just individual processes, but the entire plant. With climate-based changes in full swing and amid ongoing shifts in population density and distribution, access to safe, clean drinking water is no longer only a question for arid and remote areas. Water scarcity is affecting an increasing number of regions, people, and business- es. In this context, desalination is a vital technology to meet water demand, reduce the pressure on natural freshwater resources caused by urbanisation and growing populations, and boost water supplies by increasing water quality. As a result, the number of desalination plants in operation continues to grow. An estimate from 2018 placed the global number of operational desalination plants at 16,000, and since then, substantial capacity has been added through both expansion of existing desalination plants and the construction of new ones. Moreover, countless small desalination plants exist for industrial purposes or to satisfy local demand. Such micro desalination plants operate not only in the municipal water production industry but also in many other industries such as textiles, leather, and food. As proof of the changing patterns of water scarcity, desalination plants are being built not just in the Middle East and western Asia, but around the globe. California currently has more than 10 desalination facilities in operation, and desalination is also becoming a significant contributor to the water supply in South America and Asia.

Although the market is growing steadily, it is at the same time subject to enormous cost pressures. Not only numerous plants are currently under construction, but the plants themselves have become larger, with at least a dozen mega plants, each producing more than 500,000 cubic metres of water per day, already operating or planned. Scaling up helps desalination plants produce water more cost-efficiently over time, but the construction of mega plants requires a substantial initial investment. To achieve optimal plant performance and return on investment, the industry needs to streamline the design, construction, commissioning, and operation of desalination plants. Greenfield projects need to be executed as smoothly as possible, challenging the industry to find new ways of engineering and commissioning plants. Plants in operation need to keep costs under control and perform at maximum efficiency to minimise their energy and environmental footprint. To achieve all of this, the industry needs to draw on a resource that is often undervalued and unexploited; plant and process data can help optimise processes on every level, from automation to performance to operation.

Utilising a digital automation twin

Using a data-based simulation of a plant’s automation and control systems, OEMs, EPC contractors, and plant operators can create a digital twin of the automated processes to streamline the entire plant’s design, commissioning, and operator training. For example, simulation during the engineering phase enables troubleshooting through early testing. Simulation tools such as Simit software from Siemens provide a real-time simulation environment for comprehensive and convenient checks of the automation program, without the need to test it on a physical system.

Moreover, the digital automation twin also enables virtual commissioning of the plant, reducing on-site work, and expenses, drastically. In some cases, it is even possible to commission a plant remotely, not only significantly reducing travel expenses but also helping OEMs and EPC contractors optimally allocate to each project their available resources of expert knowledge. The digital twin of automation can also be used for simulation-based operator training. This way, operators can not only get familiar with a new plant even before the physical equipment is installed, but also use a safe training environment to test, adapt, and optimise work routines as well as prepare for critical situations. As a result, the digital twin of automation contributes to significantly reduce project lead times, and its modelling and simulation also help reduce unplanned costs during construction as well as operation.

Paving the way for a digital operation twin

Modelling and data-based decision making can also help improve plant performance and operations. For this purpose, Siemens offers two complementary solutions that prove beneficial for both desalination plant operators and constructors. The first is a digital twin of the plant management system, which allows a plant to operate at a higher level even with modest investment efforts. Such a twin also helps increase the transparency of plant operations for easier plant and process management. It enables operators to model and monitor plant performance based on accurate data and to calculate KPIs to support decision-making and improve plant operations. In short, data transparency can help operators make optimal use of available resources and capacity. In a recent project, for example, a plant management system jointly developed by Acciona and Siemens helped fine-tune processes, enabling an existing desalination plant to produce above its nominal capacity and thus avoiding the need for additional investment. In this way, the benefits of digitalisation can be utilised along the entire plant and process life cycle, from design and engineering to commissioning to operation.

Simulation tools: a digital performance

twin

Complementing the digital twin of automation, Siemens is offering model-based optimisation software that captures fundamental knowledge about a process – its physics, chemistry, control philosophy, operating policy, feedstock and energy costs, and product prices –in the form of mathematical models and their associated data. A system of such models can then be used in conjunction with state-of-the-art mathematical techniques to analyse and optimise process design or operation, improve plant ef- ficiency, reduce energy consumption, and even optimally schedule cleaning processes. In desalination plants, such models can be used to optimise multiple operational KPIs and parameters, for example, the consumption of energy and chemicals in relation to water output, production costs, and resource efficiency. Moreover, modelling can help identify optimal operation and cleaning parameters to maximise water output while preventing module failures.

The gPROMS process modelling environment from Siemens, for example, makes it possible to optimise plant performance to minimise consumption of electrical power or chemicals, or to minimise fluctuations in water quality. The modelling environment encompasses the entire physical and chemical process in rigorous, equation-based mathematical (white-box) models, which are trans- parent to the user and can be adapted and modified for different plant sizes or processes. The software lets users create a robust, reliable digital twin that supports a dynamic modelling of the process.

Moreover, white-box models do not rely on large amounts of training data for their optimisation, as do AI-based models. Consequently, they can be set up without access to large databases of either historical or generated process data. Such data are needed only to tailor the model to the specific plant or process, and to validate the model’s performance in representing the physical plant. The gPROMS environment can be used both online, with a connection to the plant process control system, and offline. When used online, the digital performance twin can run parallel to plant operation and use current control system data to make recommendations for operators, for ex- ample, on the best strategy to improve a given KPI (such as minimising energy consumption). Thus, the model supports informed decision-making and helps operators improve the overall operational effectiveness of desalination plants.

Closing the data gap through expertise and technology

So why are many desalination plants still not making use of their plant and process data? As in many industries, one culprit is the lack of data integration. To overcome the challenges posed by isolated databases and systems, the industry needs to make use of state-of-the-art technologies for data exchange and networking, and it needs to deploy secure, industry-grade solutions. Choosing suitable partners and technologies is essential to reap the full benefits of digitalisation and automation, and to be able to create a digital twin for each of the user’s respective needs and purposes.

With its broad portfolio and solid industry expertise, Siemens can address critical aspects of Industry 4.0, such as integrated engineering and integrated operations, cloud connectivity with the open Internet of Things operating system MindSphere, and dedicated applications for data analysis and processing in the cloud. Moreover, Siemens can draw upon its solutions for process monitoring and control that are tailored to the water industry and have proven their worth in numerous desalination plants. Examples include plants in Saudi Arabia, such as the Al-Khobar 1 and Al Khafji seawater reverse osmosis (SWRO) desalination plants (the latter solar powered), not to mention eight SWRO desalination plants spreading over a distance of 1,800 kilometres along the Red Sea coast of the Kingdom.

Finally, Siemens can also provide a diverse set of financing solutions for investments in future-proof technologies in key areas such as automation, digitalisation, and sustainability. One project to benefit from Siemens as a financial service partner is the Taweelah desalination plant in the United Arab Emirates, which will supply 910,000 cubic metres per day of water, meeting the water needs of 350,000 households. It is currently the world’s largest RO plant.

As these examples show, Siemens provides all the tools desalination plants require to enter the digital age with minimal risk – and finally exploit the treasure trove of plant and process data to increase

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