Abstract
The solid nature of coal presents greater difficulties in measuring and controlling the combustion process compared to gas and oil fired power plants. Knowing the composition and energy content of coal can be very useful for combustion control in coal-fired power utilities. In this work, an attempt is made to establish relationships between the hydrogen composition of coal and available data from the proximate analysis. In the present work, artificial neural network based model is developed for the prediction of hydrogen content. For practical implications, a combustion control system utilising the neural network based model is also proposed to show the potential for coal-fired utilities.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
