Abstract
Ash, as one of the by-product of combustion either accumulates onto boiler tubes as slag or is collected by electrostatic precipitators attached to the backend of the boiler. Flue gas will transport these ash particles either to the inner surfaces of the boiler or to the dust collecting facilities at the backend of the boiler. Sintered ash deposits formed in the radiant section of the boiler are known as clinkers and they contribute to a wide variety of problems to the boiler. Preventative measures to combat clinker formation is in dire need to the energy sector. In this study, a prediction model using real plan data was developed for detection of clinker formation conditions. Several variations of Artificial Neural Networks were tried and test, with emphasis given on the feed-forward neural network, cascade neural network and recurrent neural network. In addition, sensitivity analysis was also conducted to determine the influence of random input variables to their respective response variables. The Tornado Diagram is selected as the method to determine the most influential parameter for clinker formation. It is expected that the Recurrent Neural Network prediction model and the identified most influential input parameter for clinker formation will assist operators in decision making for the maintenance of boilers.
Highlights
The discovery of electricity is one of the greatest achievements of man, existence of power plants for the generation of electric power from resources such as coal and gas is of utmost importance as it has become a part of modern life
Operational problems occur as a result of high inorganic constituents that are present in coals [1]
The objectives of this study was achieve by determining the best artificial neural network (ANN) models to represent clinker formation conditions inside the boiler
Summary
The discovery of electricity is one of the greatest achievements of man, existence of power plants for the generation of electric power from resources such as coal and gas is of utmost importance as it has become a part of modern life. Pulverised coal combustion is known to be the mostly widely used technology for producing electricity across the world over the last several decades. Operational problems occur as a result of high inorganic constituents that are present in coals [1]. Coal is known to be a mixture of combustible solid hydrocarbon and incombustible mineral matter. When pulverised coal is combusted, the mineral matter in the coal transforms into ash during combustion. These ash particles are entrained in the flue gas flow along the furnace domain and impact on the furnace wall surfaces during their passage through the boiler. The amount and type of inorganic constituents play a major role in the design, maintenance and availability of coal-fired plants. The ash deposition problem is dependent on fuel composition, boiler design and operating conditions [3]
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