Development of fuzzy based methodology to commission co-combustion of unprepared biomass on chain grate stoker fired boilers
- Authors: Thai, Shee Meng , Wilcox, Steven , Chong, Alex , Ward, John , Proctor, Andrew
- Date: 2011
- Type: Text , Journal article
- Relation: Journal of the Energy Institute Vol. 84, no. 3 (2011), p. 123-131
- Full Text: false
- Reviewed:
- Description: This paper describes the development of an intelligent commissioning system to enable operators to maximise the utilisation of unprepared biomass by combusting the biomass with the minimum amount of support fuel to achieve a desired boiler output and thermal efficiency on chain grate stoker fired boilers. Tests were conducted on a 0.8 MWth chain grate stoker fired hot water boiler to investigate the combustion of different types of biomass blended with a support fuel over a wide range of boiler operating conditions and biomass moisture contents. The commissioning system was developed using fuzzy logic and expert system type rules developed while gathering the experimental data. The system was validated on untested blends of unprepared biomass with two support fuels where it was shown that it is possible to efficiently burn unprepared, high moisture content biomass with a support fuel on a chain grate stoker. This system could enable operators of chain grate stoker fired boilers to maximise the use of unprepared biomass fuels by enabling them to burn any suitable unprepared biomass by estimating the biomass moisture content and density. © 2011 Energy Institute.
Detecting burner instabilities using joint-time frequency methods whilst co-firing coal and biomass
- Authors: Valliappan, Palaniappan , Thai, Shee Meng , Wilcox, Steven , Ward, John , Tan, Chee Keong , Jagietto, Krzysztof
- Date: 2011
- Type: Text , Conference paper
- Relation: ASME/JSME 2011 8th Thermal Engineering Joint Conference, AJTEC 2011
- Full Text: false
- Reviewed:
- Description: Conventional coal-fired burners are designed to operate within specific limits that, in part, result from the need to efficiently burn the fuel. These designs have been developed to ensure stable combustion, lower NOx emissions and increase the combustion efficiency through techniques such as air staging and adding swirl to the combustion air. Recent requirements to reduce CO 2 emissions from coal-fired boiler plant has focussed on the co-firing of biomass, primarily wood, either by delivering the pulverised biomass with the coal or through separate burners. To date this approach has typically taken place at substitution levels of around 5% by mass and at these levels the operation of the burners and boiler is not adversely affected. However, as the proportion of biomass increases the fuel characteristics of the blend moves further away from the burner design parameters. This can lead to combustion instabilities and in extreme cases extinction of the flame. In order to co-fire higher concentrations of biomass a system or technique is required that can detect the onset of these instabilities and warn before the combustion conditions become dangerous. In this paper a novel technique based around the Wigner-Ville transform is presented that shows promise at being able to temporarily resolve the conditions that could result in the onset of burner instabilities for three cases; the first will present results from the combustion of 100% bituminous coal, whilst the second and third cases will present the results from experiments where the proportion of biomass was set at 10% and 20% by mass with the same bituminous coal. In each experiment the secondary combustion air was first reduced from a nominal stable condition and then subsequently increased from the same stable condition. It was found that the Wigner transform was able to resolve flicker frequency changes as the airflow rate was reduced. These changes were subsequently used in a neural network to automatically detect drastic changes in the air flow rates to the burner and could provide a means by which utility operators could detect dangerous flame instability conditions in real-time. Copyright © 2011 by ASME.
Development of an intelligent flame monitoring system for steel reheating burners
- Authors: Thai, Shee Meng , Wilcox, Steven , Tan, Chee Keong , Ward, John , Andrews, Graham
- Date: 2012
- Type: Text , Journal article
- Relation: Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy Vol. 226, no. 8 (2012), p. 1014-1031
- Full Text: false
- Reviewed:
- Description: This article describes the development of a system to indirectly monitor the combustion characteristics of individual burners based on measurement and analysis of the signals detected from photodiodes detecting flame radiation signals. A series of experiments were conducted on a 500 kW pilot-scale furnace and on two 4 MW industrial burners located in two steel reheating furnaces. The flame radiation signals were monitored using a lens that transmitted the flame radiation to ultraviolet, visible and infrared photodiodes through a trifurcated optical fibre. The experiments covered a wide range of burner operating conditions including; variations in the burner load and excess air levels and simulations of burner imbalance. The relationships between the dynamic flame radiation signals and the burner operating parameters and conditions were made off-line using neural network models. The present work indicates that the measurement of flame radiation characteristics, coupled with neural networks, provides a promising means of monitoring and adjusting burner performance. © IMechE 2012.