Performance Evaluation and Parametric Optimization of Coal-Fired Water Tube Boiler Using the Grey-Taguchi Method

Abstract

Industries, district heating companies, and public institutions that use boilers for heating, processing, or power production find it challenging to run at peak efficiencies due to rising fuel prices. Insufficient heat energy production and distribution through boilers contribute to an overall increase in energy expenditure. The performance of a boiler is affected by various controlling parameters, including specific fuel consumption capacity, load, and heat losses. The current study was conducted to evaluate the performance of the coal-fired water tube boiler at D.G. Khan Cement Company Limited, Pakistan. The experimental results were validated with artificial neural network- (ANN-) based predictions, which were observed to have an error of 14% in the regression plot. In this study, the performance parameters of the boiler, including steam temperature (ST), steam pressure (SP), and specific steam flow rate (SSFR), were optimized against fuel consumption (FC) and load using the Grey-Taguchi method. The best-performing parameters, with the best criteria, were observed at an overall grey relational grade (OGRG) of 0.891 and a load of 66%. The findings indicated that the overall performance of the boiler was optimized with an FC of 3.09 kg/s, a load of 66%, ST of 532°C, SP of 9.93 MPa, and SSFR of 21.38 kg/s.