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Pattanayak L.,Steag Energy Services India Pvt. Ltd
International Journal of Power Electronics and Drive Systems | Year: 2015

In this study an exergy analysis of 88.71 MW 13D2 gas turbine (GT) topping cycle is carried out. Exergy analysis based on second law was applied to the gas cycle and individual components through a modeling approach. The analysis shows that the highest exergy destruction occurs in the combustion chamber (CC). In addition, the effects of the gas turbine load and performance variations with ambient temperature, compression ratio and turbine inlet temperature (TIT) are investigated to analyse the change in system behavior. The analysis shows that the gas turbine is significantly affected by the ambient temperature and with increase there is decrease in GT power output. The results of the load variation of the gas turbine show that a reduction in gas turbine load results in a decrease in the exergy efficiency of the cycle as well as all the components. The compressor has the largest exergy efficiency of 92.84% compared to the other component of the GT and combustion chamber is the highest source of exergy destruction of 109.89 MW at 100% load condition. With increase in ambient temperature both exergy destruction rate and exergy efficiency decreases. © 2015 Institute of Advanced Engineering and Science. All rights reserved. Source

Pattanayak L.,Steag Energy Services India Pvt. Ltd | Sahu J.N.,University of Malaya | Sahu J.N.,Brunei Institute of Technology
Asia-Pacific Journal of Chemical Engineering | Year: 2015

Steady state concept has relevance in many fields, particularly in economics, engineering and thermodynamics. In a steady state system, the recent observed behavior will continue to be so in future. Energy and exergy analysis (first and second law of thermodynamic) in steady state condition of a thermal power plant provides in-depth information to find out areas for potential improvement in efficiency. This study deals with the performance analysis of a pulverized coal fired power plant using energy and exergy analysis in steady state condition. The overall plant performance is assessed by undertaking detailed modeling and simulating thermal cycle of the plant scheme. Off design energy and exergy utilization efficiencies and thermodynamic properties are assessed from the model simulation based on actual operating data collected from the plant Distributed Control System (DCS) at operating load of 460MW on 15-min average for a period of 8h. The analysis revealed that the combustion chamber and boiler are the major source of exergy destruction with 40.29% and 53.20% respectively. Whereas gross energy and exergy efficiency of overall plant are calculated as 34.33% and 31.47% at 460MW gross generation as compared to the design rating of 37.77% and 34.53% respectively at 500MW. This paper deals with methodology and assessment of exergy destruction in the plant and how to reduce it. Simultaneously a comparison has been made of energy losses vis-a-vis exergy destruction of various plant components, which brings out advantages of using exergy method over energy method calculation. Copyright © 2015 Curtin University of Technology and John Wiley & Sons, Ltd. Source

Pattanayak L.,Steag Energy Services India Pvt. Ltd | Ayyagari S.P.K.,Steag Energy Services India Pvt. Ltd | Sahu J.N.,Brunei Institute of Technology
Clean Technologies and Environmental Policy | Year: 2015

In a conventional coal-fired boiler combustion of coal causes buildup of soot, ash, and slag in the heat transfer surfaces, which reduces the heat transfer as well as operating efficiency. To achieve a high operating efficiency and improving heat transfer in boiler pressure parts, sootblowing is an important phenomenon in boiler operation. Boiler operators are typically provided with little or no information about the fouling status of heating surfaces or with much guidance regarding how to optimize sootblowing operations even if there are some indications like metal temperature, sprays. This raises the requirement of sootblowing optimization strategy to determine which portions of the boiler to clean and on what schedule. The objective of this study is to develop a sootblowing optimization system that uses thermodynamic model and artificial neural networks model to predict the effectiveness of heating surfaces. In addition, the system utilizes an optimization algorithm to refine the search for the optimal sequence of sootblower frequency and achieve boiler performance targets. © 2015 Springer-Verlag Berlin Heidelberg Source

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