Optimization of Temperature of Circulating Fluidised Bed Combustion Boiler Using Conventional Techniques Anova and Rsm

Abstract

In recent years, significant advances have been made in understanding and predicting the behavior of ash in combustion and gasification systems. In CFBC boilers ash sintering may contribute to deposit formation in the cyclone, return leg and post cyclone flue gas channel. Rapid sintering can lead to heavy agglomerate formation, which may finally inhibit circulation in dense phase areas (such as seal pot and return leg). Hence understanding the sintering behavior before the coal is used, would be desirable for avoiding problems.

The present work is aimed at determining the influence of operating parameters on the temperature of circulating fluidized bed boiler. Ranking given to operating parameters by observing their contribution in the temperature of boiler by combustion of coal. A design of experiments technique was adopted in the form of Taguchi’s L9 orthogonal array. The selected parameters were coal mass flow rate, coal particle size, primary air velocity and secondary air velocity. The combustion has done in modelled CFBC boiler using three quality lignite coal to analyze the temperature. The results were then analyzed and the major contributing factor towards temperature of boiler was found out based on the Analysis of Variance (ANOVA) and Response Surface Methodology (RSM) calculations. Boiler combustor temperature value optimized at targeted temperature value (1220 K) by using above method. The general trend indicates that as the temperature increases the possible of ash agglomeration in those area increases. Ash shows their sticky behavior if combustor temperature increase beyond the Ash fusion temperature ( > 1400 K ). Agglomeration of the bed material manifests itself in various forms within the combustor and associated system components. Ash deposition in the utility boilers is a major problem that may result in decreased efficiency, unscheduled outages, equipment failures, increased cleaning, and high maintenance costs. So this study helped to find out optimum condition for process parameter and to control boiler temperature.