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HIGHLIGHTS
- Digitalization of power plants results in generation of operational, enterprise, and other data types, adding an edge to business operation optimization and asset performance management.
- Digital twin solutions backed by IoT, AI, cloud, and advanced data analytics serves as a catalyst to improve the performance of power plants.
- Digital twin employs models that are trained using the past plant data and algorithms to predict the plant behavior at present and make prescriptive decisions for optimizing plant performance.
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Driving sustainability with Digital Twin
Power generation alone contributes to over 41% of the global carbon dioxide emissions, largely fueled by coal. Despite several sustainability actions set in motion, coal is expected to provide at least 22% of global power even in 2040, accounting for nearly 68% of emissions. Applying right technologies will help thermal power plants reduce up to two gigatons of CO2 emissions.
Digital twin solutions backed by internet of things (IoT), artificial intelligence (AI), cloud and advanced data analytics serve as catalysts to improve the performance of power plants across functions. These could include monitoring of equipment and processes, optimizing operations in real time, and improving availability. Digital twin solutions can assist in better operation and maintenance of applications such as boiler, gas turbine, flue gas desulfurization system, selective catalytic reduction system, and air preheater.
The solutions not only reduce CO2 and greenhouse gas emissions, but also bring down annual operational and maintenance expenses by at least $60 million.
Technology to cut thermal emissions
The need to abate global warming mandates prudent usage of fossil fuels. Coal powered thermal power plants are under pressure to perform efficiently and reduce emissions. Currently, the power generation sector alone is responsible for nearly 41% of global CO₂ emissions, with coal power being the largest contributor of nitrogen oxides (NOx), Sulphur oxides (Sox), mercury (Hg) and particulate matter. Increased deployment of carbon capture, sequestration, and utilization (CCUs) technologies can improve the sustainability quotient but may be insufficient to meet the climate goals set in the Paris agreement. Coal is still expected to provide 22% of global power and account for 68% of carbon dioxide (CO₂) emissions even in 2040.
Leveraging the right technology can help thermal power companies reduce up to 2 gigatons of CO₂ emissions. Adoption of the latest digital technologies can help improve thermal plants’ performance by reducing the consumption of fuel, auxiliary power, consumables, and greenhouse gas emissions. Existing thermal power plants, therefore, need to be equipped with these technologies to mitigate global warming.
Challenges with thermal power plants
Thermal power plants consist of large and complex equipment for power generation such as pulverizers, boilers, steam turbines and gas turbines. Pollution control equipment like selective catalytic reduction (SCR) converters, flue gas desulphurization (FGD) units, electrostatic precipitators as well as efficiency improvement equipment like air preheaters (APH), condensers and cooling towers make up its landscape.
Even with advanced control systems in place, monitoring, optimizing performance, and periodic maintenance of these equipment becomes challenging due to:
Complex plant dynamics
Interconnected equipment with interacting operations
Variability in coal quality due to diverse sources and inadequate blending
Flexibility to accommodate transient and sharp variations in power demand
Gradual degradation and faults of equipment over time
Tightening and evolving emission standards and safety regulations
The graphic below illustrates the various aspects of power generation, their data sources, and the challenges they pose.
Given the complexities and scale of operations across these plants, it is imperative to take decisions in real-time, as delays lead to huge losses and catastrophic events. There is still considerable dependence on operator expertise for running the plants. Operators take decisions based on heuristics that often result in sub-optimal operation, leading to higher cost of operation and emissions.
Delivering value through digital technologies: An opportunity
Implementation of the latest digital technologies encompassing the internet of things (IoT), artificial intelligence (AI), and advanced analytics play a critical role in improving the performance of thermal power plants. Equipment manufacturers, utility companies, and consulting firms have recently launched and deployed digital platforms to address various needs of power utilities.
Performance optimization challenges faced by thermal power plants and sources of data in a power plant
Digitalization of power plants has resulted in the generation of huge amounts of operational, enterprise, and other data types. This can be effectively leveraged for business operations optimization and asset performance management. Specific examples of creating value while guaranteeing sustainability by leveraging digital technologies are listed in listed below:
Leveraging digital technologies for sustainable operation of thermal power plants
Digital twin solutions for thermal power plants
A digital twin is a cyber-physical system that replicates the behavior of the real-life physical system while maintaining its communication with the actual system in real-time and makes recommendations to improve the plant operations as illustrated in the graphic below. It employs models that are trained using the past plant data, and state-of-the-art algorithms to predict the plant behavior at present and make prescriptive decisions for optimizing plant performance. It uses physics-based predictive models to improve the accuracy of some complex processes.
A schematic representation of a digital twin system for a power plant
Digital twin solutions address optimization of key performance indicators (KPI) that have conflicting goals and constraints at the equipment, plant, and site levels. Advanced industrial analytics with optimization and control can help solve complex multi-objective decision-making using IoT and the cloud.
Some of the applications where a digital twin can make a difference for improving the plant performance and reducing emissions are described and summarized below in the graphic.
Boiler digital twin
A boiler in a 1,000 MW unit consumes close to 9,000 tons of coal per day and causes nearly 76% of the NOx emissions in the United States. Improving and maintaining the efficiency of boilers and existing thermal power plants can reduce emissions. The challenge is to identify optimum operation settings in real-time, in response to variations in fuel properties and fluctuating power demand.
A digital twin of the boiler can utilize the power of IoT, AI, and digital technologies to detect the change of coal. Sensing environmental conditions and power demand, the twin can identify an optimum operation strategy to maximize heat rate and minimize emissions from the boiler. Boiler digital twins can reduce 8-10% of outgoing NOx and cut coal consumption by approximately a million dollars annually. These improvements also result in reduced load on emission control equipment, lower usage of reagents/chemicals, and lower auxiliary power consumption. Digital twins can benefit industrial boilers as well as captive power plants.
Combined cycle gas turbine (CCGT) digital twin
Combined cycle power plants are among the cleaner fossil fuel-powered plants. Their fluctuating power demand makes them operate at lower thermal efficiencies and susceptible to process faults. Digital twins of CCGT power plants can learn process dynamics and recommend optimum settings in real-time to improve the thermal efficiency by 0.4-0.6%. Additionally, the predictive maintenance module of the twin can prevent catastrophic failures through early fault detection and dynamic root cause analysis. The CCGT power plants enabled by digital twins ensure substantial benefits in terms of operating costs and emissions.
Flue gas desulfurization (FGD) digital twin
Coal-fired power constitutes almost 90% of the SO₂ generated from power sources in the United States, making it imperative to run FGD unit optimally. FGD operations are expensive due to the power and chemical requirements. The challenge is to adjust the operation of FGD to reduce the pumping cost and limestone usage without compromising its SOx removal efficiency and maintaining pH levels of limestone slurry in the tank. A digital twin can identify the optimum operating conditions needed to deliver consistent SOx removal efficiency. Such real-time optimization can reduce the overall energy and material costs by up to $30 million annually for a 1,000 MW plant.
APH-SCR digital twin
Selective catalytic reduction (SCR) units use a series of catalyst beds to facilitate the reduction of incoming NOx from the boiler via chemical reactions with a reagent like ammonia. The catalyst effectiveness gradually decreases due to process conditions, aging, chemical poisoning, and deposition of ash from the flue gases. This results in driving up the harmful emissions of mercury, sulfur trioxide and ammonia. The increased ammonia slippage accelerates fouling or clogging of downstream equipment called air preheater (APH). A clogged APH means reduced boiler thermal efficiency and increased power consumption by fans. Prolonged fouling may result in a forced plant shutdown for APH cleaning and generation of hazardous cleaning effluents. Monitoring the condition of SCR catalyst beds and APH clogging are critical problems.
A digital twin of an SCR-APH system can learn the catalyst degradation and APH clogging patterns from historical data. AI models can be used to identify optimal timelines and schedules for catalyst replacement. The advanced forecasting models for APH fouling can provide an optimum operation strategy to eliminate forced plant shutdowns and reduce the fan power consumption.
Instances where digital twin technology can make a difference
Toward a sustainable future for thermal power plants
In 2019, it was assessed that about 43.1 billion tons of CO₂ was emitted into the atmosphere due to human activities. Drastic actions are necessary to achieve the goals of the Paris agreement to limit the rise of global temperatures to 2°C. While the world increasingly adopts renewable energy, thermal power plants will continue to play a crucial role for a few more decades.
Today, power plants are increasingly embracing digitalization and are primed for reaping its benefits. Unfortunately, many of these solutions have been limited to dashboards, automated reports, and a few isolated digital use cases. Digital twin technology must become ubiquitous across the thermal power industry to ensure reduced carbon footprint and minimal emissions along with improved energy security and availability across the world.
