Performance prediction of marine intercooled cycle gas turbine based on expanded similarity parameters. (15th February 2023)

• Record Type: Journal Article
• Authors: Cheng, Xianda; Zheng, Haoran; Dong, Wei; Yang, Xuesen
• Is Part Of: Energy. Volume 265(2023)
• Publication Date: 2023-02-15
• Subjects: Performance prediction -- Gas turbine -- Intercooled cycle -- Buckingham's Pi theorem -- Simulation model; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2022.126402
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The performance of marine intercooled cycle gas turbines (ICGTs) is affected by atmospheric and sea conditions. Gas turbine operators have to rely on complicated and unfriendly simulation models to predict the performance of ICGTs under different ambient conditions. Aiming at this problem, this paper introduces a novelty fast prediction method based on similarity theory, which can help gas turbine operators realize performance parameters prediction of ICGTs on the spot. For this purpose, the similarity theory is firstly extended to ICGTs. The similarity parameters corresponding to seawater flow rate, glycol solution flow rate, and seawater temperature are derived using Buckingham's Pi Theorem. On this basis, the performance prediction formula of ICGTs is developed. The second-order and dissimilar effects of ICGTs are fully considered in this formula to improve the prediction accuracy. The values of the unknown coefficients in the formula can be obtained by fitting from a small amount of test data. Finally, the high-fidelity ICGT simulation model and the actual ambient conditions verify the proposed method. The results show that the proposed method has good practicability and accuracy, which provides a new approach to predicting marine ICGT performance. Highlights: The similarity theory is expanded for the intercooled cycle gas turbine. A novelty fast prediction method of the ICGT performance is presented. A high-fidelity simulation model is established. The proposed method can conveniently and effectively predict the ICGT performance.