HEATING TECHNOLOGY


AI algorithms quickly analyse data and adjust the combustion process to optimise performance in real-time


efficiency and energy savings, as well as reduced emissions.


Real life examples Industrial applications of AI in combustion control systems are varied. In power generation, AI can help utilities optimise the combustion of fossil fuels and integrate renewable energy sources such as wind and solar. For example, AI can be used to predict wind and solar availability and adjust the combustion process accordingly to optimise energy output.


In oil and gas processing, AI can


help companies optimise the refining process and minimise emissions. AI algorithms can analyse data from sensors and optimise the combustion process to reduce emissions of pollutants such as nitrogen oxides (NOx) and sulphur dioxide (SO2). In industrial heating, AI can help


Artificial Intelligence can help to optimise combustion control systems


An exploration of the potential role of artificial intelligence in enhancing the capability of combustion control systems.


Martin Thirsk


Managing Director of Energy Technology & Control


www.energytechnology control.com


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ombustion control systems are critical components of industrial processes that require combustion, such


as power generation, oil and gas processing, and industrial heating. These systems regulate the air- fuel ratio, temperature, and other parameters to ensure efficient and safe combustion. In recent years, artificial intelligence (AI) has emerged as a powerful tool for optimising combustion control systems and improving their performance. One key application of AI in


combustion control systems is predictive maintenance. Predictive maintenance involves using data from sensors, machine logs, and other sources to detect patterns and anomalies that could indicate potential equipment failure.


By analysing this data with AI algorithms, maintenance teams can identify issues before they become serious and take proactive measures to prevent equipment failure. This can minimise downtime and reduce maintenance costs, while also improving safety and reliability.


Fuel optimisation Another application of AI in combustion control systems is optimisation of fuel usage. By monitoring fuel consumption and combustion efficiency in real-time, AI algorithms can adjust the air-fuel ratio, fuel injection timing, and other


parameters to maximise energy output and minimise emissions. This not only reduces operating costs but also helps companies meet regulatory requirements and reduce their carbon footprint.


Data analysis One of the key benefits of AI in combustion control systems is its ability to adapt to changing conditions. Industrial processes can be complex and dynamic, with many variables affecting combustion performance. AI algorithms can quickly analyse data and adjust the combustion process to optimise performance in real-time. This can lead to significant improvements in


companies optimise the combustion of biomass, waste, and other alternative fuels. By adjusting the air-fuel ratio and other parameters, AI algorithms can improve combustion efficiency and reduce emissions.


Looking ahead The role of artificial intelligence in combustion control systems is becoming increasingly important in industrial applications. By enabling real-time optimisation and predictive maintenance, AI can help companies improve efficiency, reduce emissions, and enhance safety in a wide range of industrial processes. As technology continues to evolve, AI is poised to play an even greater role in the future of combustion control systems. ■


One of the key benefits of AI is its ability to adapt to changing conditions


In utilities, AI can predict wind and solar availability to adjust the combustion process EIBI | FEBRUARY 2024


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