Abstract
This study focuses on the performance optimization of steam turbine inlet parameters using regression analysis. The input parameters considered are mass flowrate, temperature, and pressure, while the output parameters include power output, electrical efficiency (EE %), and overall efficiency (OE %). The analysis begins with the application of best subsets regression to determine the most influential variables on OE %. The results show that the best regression model includes mass flowrate, temperature, and pressure as significant predictors. The regression analysis further investigates the relationship between OE % and the selected input parameters. The analysis of variance (ANOVA) with a p-value of 0.003, the regression model is statistically significant. Among the predictors, mass flowrate has the most substantial impact on OE %, having a p-value of 0.001. Temperature, in contrast, does not exhibit a significant effect on OE %, as indicated by its p-value of 0.128. The coefficient values indicate that an increase in mass flowrate results in a higher OE%, while temperature has a relatively smaller impact. The results also indicate that mass flowrate and temperature significantly influence overall efficiency, while pressure has minimal impact. A two-parameter regression model comprising mass flowrate and temperature demonstrates a better fit than a three-parameter model. The two parameter regression model indicates that the plant achieves its highest overall efficiency of 64.91% when operating with a mass flowrate of 83t/h at 510 °C, while the experimentally determined overall efficiency is 63.16%. Overall, this study demonstrates the use of regression analysis to optimize the performance of steam turbine inlet parameters. The findings provide insights into the influence of mass flowrate and temperature on OE %, allowing for informed decisions regarding steam turbine operation and efficiency improvement.
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Abbreviations
- FW:
-
Feed water
- Fi:
-
Fuel energy input [kW]
- h:
-
Specific enthalpy [kJ/kg]
- Pi:
-
Inlet pressure [kgf/cm2]
- Qi:
-
Heat input [kW]
- Qo:
-
Heat output [kW]
- Qu :
-
Process heat [kW]
- ms :
-
Mass flowrate of steam [t/h]
- Ƞo:
-
Overall efficiency [%]
- Ƞo:
-
Overall efficiency [%]
- t/h:
-
Ton per hour
- N.C.V:
-
Net calorific value
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Sumanraju, V., Rao, T.R. & Sanke, N. Optimization of process parameters for enhancing overall efficiency: experimental analysis and regression modelling. Int J Interact Des Manuf (2023). https://doi.org/10.1007/s12008-023-01626-9
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DOI: https://doi.org/10.1007/s12008-023-01626-9