Searching for the Most Suitable Loss Model Set for Subsonic Centrifugal Compressors Using an Improved Method for Off-Design Performance Prediction

This work investigates loss model sets based on empirical loss correlations for subsonic centrifugal compressors. These loss models in combination with off-design performance prediction algorithms make up an essential tool in predicting off-design behaviour of turbomachines. This is important since turbomachines rarely work under design conditions. This study employs an off-design performance prediction algorithm based on an iterative process from Galvas. Modelling of ten different loss mechanisms and physical phenomena is involved in this approach and is thoroughly described in this work. Geometries of two subsonic compressors were reconstructed and used in the evaluation of individual loss correlations in order to obtain a suitable loss model. Results of these variations are compared to experimental data. In addition, 4608 loss model sets were created by taking all possible combinations of individual loss estimations from which three promising candidates were selected for further investigation. Finally, off-design performance of both centrifugal compressors was computed. These results were compared to experimental data and to other loss model sets from literature. The newly composed loss model set No. 2137 approximates experimental data over a 21.2% better in relative error than the recent Zhang set and nearly a 36.7% better than the outdated Oh’s set. Therefore, set No. 2137 may contribute to higher precision of centrifugal turbomachines’ off-design predictions in the upcoming research.

Thermodynamic Modeling and Performance Simulation of Combined Cycle Power Plant Under Design and Off-Design Condition

Combined cycle power plants (CCPP) are increasingly important for safer and cleaner electricity generation. In this context it is imperative to explore options to enhance its thermal performance for its design and off-design condition. This study presents the performance comparison of two heavy-duty gas turbined (GT) based CCPP with triple pressure steam bottoming cycle. The CCPP system component is modeled using a commercial software Ebsilon and the off-design performance prediction is made using necessary component correlations. The correlations make use of normalized curves that are generated from model runs and apply the factors received from such curve to design performance to estimate the off-design performance. The model simulation is validated against literatures. Furthermore, inlet air cooling technique (IAC) is introduced in this study to enhance the CCPP power production without compromising component performance. The performance comparison of both the CCPP units are presented in an integrated manner by considering interaction of bottoming cycle on GT operation. The results are established as a function of ambient temperature based on energy and exergy principle and the power boosting and economic profit. The results also demonstrate the benefit of IAC on part-load performance. The component level exergy analysis proved that IAC improves the system exergy efficiency.