Introduction
Desalination is one of several sectors being changed by new technologies like artificial intelligence (AI) and the internet of things (IoT), which enable them to be more productive and use less energy.
The “smart desalination journey,” as we refer to the process of developing a full-scale smart desalination plant, depends on recognizing the value of data.
AI systems’ capacity for data analysis, forecasting, and improvement is a crucial pillar for advancing desalination plants’ digital transformation.
Although modern desalination facilities use computerized control systems to manage plant operations, the sector still faces a number of difficulties, most of which are connected to worker safety and production disruption.
The growing accessibility of the production data from the plant necessitates a requirement for careful examination of AI.
In order to generate predictions about the future, AI systems ingest and analyze data for correlations and patterns.
The three cognitive abilities that AI emphasizes are learning reasoning and self-correction.
AI can help the desalination sector produce more water effectively, keep workers safer and have less environmental impact.
Desalination and the industrial revolution
Desalination has undergone considerable changes as a result of the Industrial and Scientific Revolutions.
Desalination of water, which was originally carried out in a very primitive manner, is today an important factor in the provision of water in impressive quantities to nations without access to fresh water sources.
1. The first industrial revolution began in 1784, when water and steam power were used to mechanize production processes for the first time, paving the way for mass production.
2- The use of electricity, gas, and oil to increase mass production made the second industrial revolution in 1870 stand out.
3- The third industrial revolution, which began in 1969, automated the industry by introducing nuclear energy, electronics and information technology.
It refers to the period of the digital revolution when analog electronic and mechanical devices were transformed into today’s digital technology.
4-The fourth industrial revolution, sometimes known as “industry 4.0,” is currently underway.
It has been a part of the technical advancements in several important areas, such as AI, the IoT and robots, which are unquestionably influencing the future of every sector.
5. Filtration and distillation have been used to desalinate water for thousands of years.
However, complex desalination techniques were a thing of the laboratory at the time of the first industrial revolution.
6- Thermal desalination techniques became more popular throughout the second industrial revolution.
For instance, the first MSF plant with a capacity of 227.1 m3/d was built at Al-wajh and Duba, Saudi Arabia, in 1928.
7- The first commercial reverse osmosis plant was built during the third industrial revolution, which also saw the beginnings of the reverse osmosis business.
The world’s governments and engineers were interested in its new endeavor.
8- Desalination facilities can now use IR 4.0 technology like AI and IoT.
To achieve significant increases in productivity and automation, use robotics and digital twins.
Government funding is a significant component in advancing digital innovation.
Saudi Arabia’s Vision 2030 aims to build a more diversified and sustainable economy as the Middle East region transitions away from its historic heavy reliance on oil earnings and toward revenue diversification.
The Kingdom of Saudi Arabia established the Saudi Data and Artificial Intelligence Authority in 2019 with the lofty objective of making the nation a trailblazing and prosperous global model of excellence on all fronts (SDAIA).
To establish the nation as a leader in data-driven leadership, SDAIA seeks to advance the data and AI agenda.
By 2030, the monarchy also hopes to train up to 20,000 data and AI specialists and attract investments totaling $20 billion.
In order to reduce carbon emissions and enhance desalinated water production in line with Vision 2030, the Kingdom has created a number of innovations that have helped to protect the environment and the sustainability of desalinated water production.
Challenges that face the desalination industry
Desalination plants, like the majority of manufacturing facilities around the world, deal with a number of issues that impede the efficiency of operations and potentially jeopardize their longevity.
Some of these issues will be explored, including rising energy costs and emission rates, as well as equipment breakdowns and decreased labor productivity.
The creation of desalinated water requires a number of steps, beginning with the input of seawater, followed by pretreatment, during which solid waste is removed from the water, and then the major desalination stage.
In a posttreatment step, seawater is chlorinated and given a mineral boost after the salt has been removed.
Last but not least, fresh water is kept in tanks and is ready to be delivered to users.
Improved Membrane Performance
The maximum salt rejection at the lowest operating pressures is what engineers ideally aim for.
In general, as the pressure is decreased, less salt is removed from the finished water.
SWRO normally runs at pressures between 60 and 70 bar.
We could save money and energy if our membranes could continue to reject salt at pressures of, say, 50 to 55 bar, according to Lienhard.
Making membrane materials that can function under incredibly high pressures and salinities is a current research goal.
According to Stover, “this encompasses not only new membrane materials but also how the membranes are assembled and used.”
Changing Seawater Conditions
The input pretreatment system for seawater desalination facilities can get overloaded by sudden and unpredictable seawater conditions, particularly dangerous algal blooms.
In some circumstances, stand-by dissolved-air-flotation (DAF) systems can be installed for such an event, but doing so entails a significant financial outlay for a system component that might not be used frequently, according to Lienhard.
Brine Disposal
The input pretreatment system for seawater desalination facilities can get overloaded by sudden and unpredictable seawater conditions, particularly dangerous algal blooms.
In some circumstances, stand-by dissolved-air-flotation (DAF) systems can be installed for such an event, but doing so entails a significant financial outlay for a system component that might not be used frequently, according to Lienhard.
Membrane Fouling
Inorganic solutes, biofilms, and organic debris that fouls feed water all slowly build up on membranes as they operate.
The total result is a decrease in permeability, which is typically countered by a modest increase in pressure to keep the flow of water.
Over the course of the plant’s entire life, this increases both energy and water costs.
Although routine membrane cleaning shuts down the plant and creates liquid waste that must be disposed of.
Energy Recovery
Even though SWRO is the commercial saltwater desalination technique that uses the least energy, it still uses a lot of energy.
A typical system’s total operating expenses range from 35% to 40% in terms of electrical energy.
Up to 60% less energy is used when energy recovery devices (ERDs) are used.
Additionally, there are growing initiatives to integrate renewable energy.
The first large-scale solar-powered desalination plant was built and deployed by Siemens Austria in 2019.
This plant produces so much energy that extra electricity is fed into the public grid.
Higher Freshwater Recovery
Creating process designs with transient or batch activities is one strategy for enhancing RO production.
A flushing phase comes after recirculating the brine back to the membrane feed for a while.
Recirculation, according to Stover, “increases the recovery rate by boosting freshwater production and decreasing brine flow.”
Recent findings have been encouraging, with reported brackish RO recovery rates rising from the historical average of 75% to as high as 98%.
Scaling
Salts have a tendency to build on equipment surfaces at higher brine concentrations, which might halt or impede the desalination process.
Stover said that one solution to the issue is to purposefully precipitate and remove these salts before desalination or as a stopgap measure, allowing for additional desalination.
We anticipate further innovation in this area as there is a lot of work being done to incorporate precipitation into both membrane and thermal desalination processes.
Protecting Marine Life
A significant environmental problem is a harm that seawater intake systems do to marine species.
It is possible to reduce the negative effects of intake systems on aquatic organisms by using subsurface intakes.
Subsurface intakes can be useful in small systems because they also offer some pretreatment.
However, Childress noted that the installation of large systems greatly raises building costs and duration.
Additionally, the existence of suitable geology and sediment characteristics, such as sand and gravel with sufficient high porosity and transmissivity, is necessary for the installation of subsurface intakes.
Environmental impact
The steps of producing, allocating, and using water result in substantial energy usage.
Only desalination accounts for 0.4% of the world’s electricity use.
Even though RO is the commercial seawater desalination technology that uses the least energy, it still uses a lot of energy.
A major issue with desalination is high energy consumption and rising CO2 emissions.
According to some studies, the US water production industry is in charge of 5% of all carbon emissions.
From 0.4 to 6.7 kg CO2 eq/m3, the RO desalination process’ estimated carbon footprint has been quantified.
Meaning that the desalination of 1,000 cubic meters of seawater could result in the release of up to 6.7 tonnes of carbon dioxide.
AI Applications
Early Warning Jellyfish Bloom Detector
Jellyfish blooms, which are marked increases in the jellyfish population, are becoming more common in oceans all around the world.
The increase of blooms is assumed to be caused by factors such as ocean pollution, overfishing, contaminated water, decreasing oxygen levels, rising water temperatures and salinity changes.
Jelly blooms obstructing water inlets are the cause of desalination plant shutdowns.
Oceanic blooms are challenging to identify and monitor, making it challenging to act quickly.
This application’s goal is to notify plant management when jellyfish blooms are drifting close to the plant.
After that, the plant manager can start a human intervention process to lessen and prevent the harm brought on by the jellyfish bloom.
Safety and Security
Because working in desalination plants poses electrical and chemical risks, it’s critical to ensure employee safety on the job.
Incident Management
All procedures, dangers, and injury records must be digitalized during this phase.
Analyzing risk factors and prior injuries might result in the creation of a comprehensive injury strategy.
PPE compliance
To ensure that workers are wearing the proper PPE and to notify them if they are not, visual AI can be used to check the equipment.
Geo-fencing
A virtual wall for a particular physical location is called a geofence.
This device aids in preventing equipment theft and unauthorized use by sending prompt notifications whenever a piece of equipment leaves the geofence.
It might also keep an eye on staff members as they enter or leave the geofence.
Fire Hazard Prediction
systems that keep an eye on the temperature of the equipment for indications of overheating and subsequent fires.
Asset maintenance and performance management
Condition Based Maintenance
Condition-based maintenance, in contrast to conventional interval-based preventative maintenance, is only carried out when one or more indicators point to an impending failure of a piece of equipment or to a decline in its performance.
Condition-based maintenance, while proactive and not time-based, nevertheless falls within the category of preventive maintenance because it does not provide a complete analysis of the optimal time to perform maintenance.
Predictive Based Maintenance
The personnel is exposed to severe risks and continual uncertainty when asset performance management is done in a reactive manner.
The goal of predictive maintenance is to spot problems early so that they can be fixed before they become serious incidents.
Maintenance Optimization
At this point, the system uses preventative, reactive, and forecast maintenance operations to optimize and select the optimum maintenance plan (time, length, and necessary expertise).
The mobile operator device will receive the ideal schedule.
Digital twin Based Asset Maintenance
Digital twins, which are digital representations of real-world entities, are used to update the “digital twin” copy of the device’s attributes and stats in real-time using information gathered from the actual device.
A digital twin of an asset will include a 3D and mathematical model of the asset.
The operational data from the sensors can then be combined with the engineering-related parts of the asset to provide significant insights into performance or potential problems.
Digital twins can also be used to simulate processes (like RO osmosis) and alter parameters before putting them into practice in plant operations.
Virtual Simulation
Field training is time- and money-consuming and classroom education rarely simulate actual situations.
To train employees and trainees, operational operations and safety procedures will be recreated in this application using a virtual simulation and augmented reality technology.
1. Augmented Reality
By fusing digital data with the real world of physical plants, engineers can remotely assess plant operations and give instructions to actual machinery without being present.
2. Virtual Reality
The delivery of on-the-job plant training in a realistic environment without interfering with production or other employees’ activities is possible thanks to VR technology.
VR may also simulate hazardous situations to increase worker safety awareness.
3. Digital Twin VR simulation
Augmented reality (AR) can project a digital equivalent on top of a physical piece of equipment to help users understand the data coming from that device.
However, a virtual reality (VR) digital twin can be used to simulate a number of operational procedures.
Energy and Chemical Management System
The Chemicals Management System’s primary goal is to digitally track chemicals and streamline cleaning-in-place (CIP) procedures.
Consequently, enabling and offering CIP management, real-time information for consumption (of chemicals, water, time and resources), available inventory, and enabling utilization optimization.
ML algorithms can forecast energy inefficiency in energy management and notify managers when it occurs.
Chemical dosage
The system can inform the DCS operators of the recommended set points for chemical consumption based on historical consumption patterns and measurements of the water quality by continuously monitoring both the water quality using analyzers and the previous chemical consumption of material.
Energy consumption optimization
Energy IoT sensors gather data on energy use from various devices.
The data is used to produce insights about the efficiency of energy management and to suggest scenarios to reduce energy consumption.
Smart Plant Water Grid System
Desalination involves a number of energy-intensive procedures that have high financial and environmental implications.
Because of this, energy consumption efficiency is crucial for maintaining low manufacturing costs.
Therefore, it is beneficial to install artificially intelligent smart grids at the desalination plant that can reduce energy use and chemical expenses while enhancing operational efficiency.
Through the control of the various production units, this use case seeks to optimize both the energy consumption, in particular the energy consumed by high-pressure pumps and the chemical consumption.
The grid system meets the daily production objective by monitoring the consumption profile throughout the day and adjusting the on/off timing of the various components.
This smart grid system unifies all SWCC production units into one platform where AI/ML is utilized to:
• Optimize power consumption.
• Optimize chemical consumption.
• Find areas of possible savings.
• Provide recommended actions to the operators.
Warehouse Management
1. Spare Part logging
Managing inventory (e.g spare parts) in and out of the plant warehouse with barcodes and QR codes allows warehouse managers to track and review inventory in real time
2. Warehouse automation robots
Using VR systems, on-the-job plant training can be provided in an immersive environment without disrupting production or the work of other workers.
Also, dangerous situations can be simulated using VR to increase worker safety awareness.
Visual AI (Drone based platforms)
Drones can be part of desalination plants’ maintenance procedures to carry out several functions like asset inspection, defect detection and surveillance tasks.
By using a drone to collect visual data on both the physical condition of an asset and its security aspects, drone inspections can prevent inspectors from being exposed to dangerous or harsh situations.
1. Pipeline Inspection Drones
Drones can be used to inspect water transmission lines and search for any defects or leakage.
2. Produced water tank inspection
If left unattended, many common tank materials are subject to corrosion, cracking, or rusting.
Drones can obtain a detailed visual and thermal inspection of the inside of the tank and report any abnormalities found.
3. Drone Surveillance
Drones can detect any intruders/vandals either inside the plant or around the water transmission pipelines.
References
[2] Amr Mansour AI Lead| Consultants team, Mohammad Abusaad Data Consultant| Consultants team, Gayda Mutahar AI Consultant | Consultants team,smart desalination Hydrating the future using AI, Saline water conversion corporation (SWCC)
That is interesting
Thank you !