Neural network modelling and control of coal fired boiler plant

This thesis presents the development of a Neural Network Based Controller (NNBC) for chain grate stoker fired boilers. The objective of the controller was to increase combustion efficiency and maintain pollutant emissions below future medium term stringent legislation. Artificial Neural Networks (ANNs) were used to estimate future emissions from and control the combustion process. Initial tests at Casella CRE Ltd demonstrated the ability of ANNs to characterise the complex functional relationships which subsisted in the data set, and utilised previously gained knowledge to deliver predictions up to three minutes into the future. This technique was then built into a carefully designed control strategy that fundamentally mimicked the actions of an expert boiler operator, to control an industrial chain grate stoker at HM Prison Garth, Lancashire. Test results demonstrated that the developed novel NNBC was able to control the industrial stoker boiler plant to deliver the load demand whilst keeping the excess air level to a minimum. As a result the NNBC also managed to maintain the pollutant emissions within probable future limits for this size of boiler. This prototype controller would thus offer the industrial coal user with a means to improve the combustion efficiency on chain grate stokers as well as meeting medium term legislation limits on pollutant emissions that could be imposed by the European Commission. Acknowledgements First of all, I would like to express my sincere gratitude to my Director of Studies, Professor Steven Wilcox for his encouragement and continuous supervision. The completion of this PhD research would not have been possible without his patience and constant support over the last five years. Heartfelt thanks also to my second supervisor, Professor John Ward for his inspirational ideas and guidance throughout the course of my PhD program. My special thanks to Dr. Alex Chong and Dr. C.K. Tan for their constructive help especially in understanding the software development aspect of the research project. Thanks are also due to Dr. O.H. Tan for his companionship and fruitful discussion of relevant research topics over the past few years. My sincere appreciation to Professor William G. Kaye of BCURA for his enthusiasm and commitment to the project. His "tough" questions have made a number of project meetings over the last few years a memorable experience. Thanks also to Managing Director of James Proctor Limited, Mr. Andrew Proctor for his association in this project. Many thanks also to former Proctor's senior commissioning engineer, Mr. Wayne Jessop for his passionate assistance in setting up the interface communication between the control instrument and the plant control panel at the industrial chain grate. Much of the commissioning tests on the industrial boiler would not have been possible without his experience on efficient chain grate stoker operation. Thanks are also due to the staff of Casella CRE Ltd, Mr. Nigel Black for carrying out the tests at the test facility. Many thanks are also to Mr. Gareth Betteney, Senior Technical Officer in the School of Technology for his kind help and guidance during the construction of the data logging and control instrument for work on the industrial stoker boiler. Thanks also to Mr. Wayne Byrne, Senior Service Engineer of Testo Ltd, for his number of "free" guidance to diagnose and rectify the flue gas analyser. The important emission readings for the control experiments would not have been possible to obtain without his invaluable help. Finally, I would like to thanks my family, especially my parents for their love, support and encouragement throughout my study life. Thanks also to friends, in particular Molly, Alex, Lai, Teck Hin, Jacky, Eric, Priscilla and Khuan, for their warm friendship and support.