Parametric Analysis and Optimization of a Dual-Fuel-Fired Boiler for Power Generation Using the Taguchi Design Approach

Abstract

Increased energy supply reliability, environmental sustainability, more competitive businesses, and improved standard of living are all made possible by more efficient energy conversion processes. In view of this, the present study aims at analysis and optimization of the operational parameters of a dual-fuel-fired boiler using Taguchi design method to enhance boiler thermal efficiency and throughput for sustainable power generation. The L27 orthogonal array (OA) was employed with 27 experimental runs to assess the influence of the four identified design parameters: economizer outlet water temperature (EOWT), total airflow (TAF), gas air heater outlet temperature (GAHOT), and feed water temperature (FWT) on the boiler main steam flow (BMSF). Box–Behnken factorial design from Minitab 18 was used to analyze the effects of the design factors and runs on the response parameter. Results of the study reveal that the quadratic regression model developed with the Taguchi design predicted the BMSF at 95.5% confidence level. The optimal signal-to-noise (S/N) ratio of 56.57 and maximum BMSE of 674 T/h were achieved at the optimal design parameters of 257°C of EOWT, 64% of TAF, 237°C of GAHOT and FWT of 210°C at the boiler feed drum. The adequacy and degree of fitness of the quadratic models developed were determined using the coefficient of determination (R²), adjusted and predicted R², and adequate precision. The coefficient of determination R² values for the BMSF model and S/N ratio model are 0.9995 and 0.9990, respectively. The R² values show that the developed models have a good fit and ability to predict BMSF and S/N ratio accurately. In addition, adjusted R² (BMSF model: 0.9990; S/N ratio model: 0.9981) and predicted R² (BMSF model: 0.9956; S/N ratio: 0.9955) values are in reasonable agreement as their difference is less than 0.2. Conclusively, this study shows that the most influential factor on BMSF is the EOWT with a percentage contributing ratio of 38%; this is followed by FWT with 36%. From the prediction analysis and with the optimized factors, the efficiency of the existing steam turbine power plant of 33% could be increased to 55%.