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Impact of Fuel Variability and Operating Parameters on Biomass Boiler Performance

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Impact of Fuel Variability and Operating Parameters on Biomass Boiler Performance Impact of Fuel Variability and Operating Parameters on Biomass Boiler Performance by Nazanin Abbas Nejad Orang A thesis submitted in conformity with the requirements for the degree of Doctorate of Philosophy Chemical Engineering and Applied Science University of Toronto © Copyright by Nazanin Abbas Nejad Orang 2019 Impact of Fuel Variability and Operating Parameters on Biomass Boiler Performance Nazanin Abbas Nejad Orang Doctor of Philosophy Department of Chemical Engineering and Applied Chemistry University of Toronto 2019 Abstract Biomass boilers provide up to one-third of the energy requirement in pulp and paper mills by burning hog fuel, which is a mixture of wood-waste available at the mill site. The quality of this fuel varies significantly depending on its source and storage conditions. This fuel variability often causes biomass boiler operation to be unstable and unpredictable. This study consists of two parts: the first part investigates the impact of fuel variability on combustion and develops means for mitigating these impacts to achieve stable boiler operation. The second part identifies the most influential parameter in boiler operation using multivariate analysis, and develops a predictive statistical model for optimization of biomass boiler thermal performance. In the first part, wood species are differentiated by their initial particle density. For all wood species examined, particle density decreases throughout the combustion process but at different rates depending on the combustion stage. During the devolatilization stage, the density decreases significantly as a result of rapid mass loss. This sharp decrease causes particles to be light enough to be entrained and/or be lifted off from the grate by the flue gas. An analytical model is then developed to calculate particle entrainment velocity, and to determine whether a particle is entrained and if so, how much unburned mass is left upon entrainment. ii In the second part, multivariate analysis is used to identify the most important parameters in boiler operation. The results show that moisture content is the most influential parameter and a soft sensor is consequently developed to estimate the feedstock moisture content from other parameters. A predictive Partial Least Square (PLS) model is built to predict the thermal performance of a boiler in real-time and to determine the contributing factors to process upsets. In practical applications, the entrainment model is used for fuel preparation and sizing to reduce particle entrainment. The PLS model, along with the moisture content soft sensor, can be used for process monitoring providing additional insights into causes of process variability. iii Acknowledgements First of all, I would like to thank my PhD supervisors, Prof. Honghi Tran and Prof. Andrew Jones without whom this dissertation would not have been possible. Professor Tran has been and will always be my mentor and role model in life, I appreciate and will always cherish his unconditional support, irreplaceable guidance and unimaginable patience during the course of my graduate studies. Professor Jones provided a unique perspective into the practical implications of this work while also providing valuable guidance for the scientific rigor of the research. I would also like to thank my committee: Prof. Markus Bussman, Prof. Will Cluett, Prof. Nikolai DeMartini and Dr. J.Y Zhu for their guidance and support along this journey. This research has been part of a large research program undertaken by the Energy and Chemical Recovery Research Group at the University of Toronto. I would like to thank the other students in this group for their friendship and support whether it was for brainstorming, help on methodology or building a new experimental setup. This work was financially supported by a consortium of 22 pulp and paper related companies and the Natural Sciences and Research Council of Canada (NSERC). I would also like to thank the consortium members for their feedback and advice on the progression of this project. I would like to thank my family: my parents Maryam and Samad, my brothers Nima and Mehdi (and his family Aida and Bardia), my in-laws Shahla and Abi, for their unconditional love, support and always believing in me. Finally, I would like to thank my partner-in-crime Navid, without his love, kindness and words of encouragements, this journey would not have started. This dissertation is dedicated to my wonderful family. iv Table of Contents Acknowledgements ....................................................................................................................iv Table of Contents ........................................................................................................................ v List of Tables .......................................................................................................................... viii List of Figures ............................................................................................................................ix List of Appendices ................................................................................................................... xiv List of Acronyms ...................................................................................................................... xv List of Nomenclature ................................................................................................................ xvi List of Subscripts ....................................................................................................................xvii Introduction ............................................................................................................................ 1 1.1 Energy from Biomass in Pulp and Paper .......................................................................... 1 1.2 Motivation and Objectives ............................................................................................... 7 1.3 Thesis Outline ................................................................................................................. 9 Literature Review ................................................................................................................. 10 2.1 Combustion Reactions ................................................................................................... 10 2.1.1 Volatile Burning................................................................................................. 10 2.1.2 Char Burning ..................................................................................................... 10 2.2 Biomass Characteristics and Specifications .................................................................... 11 2.2.1 Moisture Content ............................................................................................... 11 2.2.2 Wood Species .................................................................................................... 12 2.2.3 Size .................................................................................................................... 12 2.3 Particle Entrainment ...................................................................................................... 14 2.4 Application of Data Analysis Techniques ...................................................................... 14 2.4.1 Soft Sensors ....................................................................................................... 15 2.4.2 Multivariate Analysis ......................................................................................... 15 v 2.5 Knowledge Gap ............................................................................................................. 16 Methodology ........................................................................................................................ 17 3.1 Thermogravimetric Combustor ...................................................................................... 17 3.2 Fixed-Bed Biomass Combustor...................................................................................... 19 3.3 Steady State Heat and Mass Balance .............................................................................. 20 3.3.1 Inlet/outlet conditions and energy losses............................................................. 20 3.3.2 Performance and Efficiency Prediction............................................................... 24 3.4 Multivariate Analysis..................................................................................................... 25 3.4.1 Principal Component Analysis (PCA) ................................................................ 25 3.4.2 Partial Least Square (PLS) ................................................................................. 27 3.4.3 Analysis of Plots ................................................................................................ 28 Effect of Wood Species on Combustion ................................................................................ 30 4.1 Elemental Analysis ........................................................................................................ 30 4.2 Particle Density ............................................................................................................. 32 4.3 Bulk Density .................................................................................................................. 37 4.4 Particle Density Modeling ............................................................................................
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