混流式涡轮转轮设计及与模型试验结果的比较

Buğra Yilmaz, Adnan Sözen, Oğuzhan Bendeş
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摘要

水力发电厂的气蚀磨损和水力效率下降一直是各种研究的主题。图尔基耶 Kızılırmak 河上的一座水电站于 1960 年开始运行,除了一般的维护工作外,至今未进行过任何大规模的修复工作。发电厂有 4 台混流式水轮机,每台功率为 32 兆瓦。多年来,由于水轮机转轮的气蚀磨损,出现了性能下降、振动和噪音问题。此外,根据 2020 年在发电厂进行的效率测量,水轮机的最高水力效率从 1960 年发电厂投产时的 92% 降至 87.9%。本研究采用雷诺平均纳维-斯托克斯(RANS)计算方法对混流式水轮机转轮的重新设计进行了计算流体动力学(CFD)分析,并根据 IEC 60193 进行了模型试验。结果表明,模型试验结果和 CFD 结果非常接近,尤其是在最佳效率点。在额定水头下,CFD 分析计算出的最大水轮机水力效率为 94.95%,而模型试验计算出的最大水轮机水力效率为 95.19%。重新设计的水轮机转轮叶片所形成的 x 形叶片确保了压力的均匀分布,并显著提高了水力效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Francis Type Turbine Runner Design and Comparison with Model Test Results
Cavitation wear and hydraulic efficiency decrease in hydroelectric power plants have frequently been the subject of various research and studies. A hydroelectric power plant built on the Kızılırmak River in Türkiye started operating in 1960 and has not been subjected to any large-scale rehabilitation work other than general maintenance until today. The power plant has 4 Francis-type turbines, each with a power of 32 MW. Due to cavitation wear of turbine runners over the years, performance loss, vibration, and noise problems have arisen. Moreover, the maximum turbine hydraulic efficiency, which was 92% in 1960, the year the power plant was commissioned, decreased to 87.9% according to the efficiency measurements carried out at the power plant in 2020. In this study, Computational Fluid Dynamics (CFD) analyses were accomplished with Reynolds averaged Navier Stokes (RANS) calculations for the redesign of the Francis-type turbine runner and finally checked by a model test according to IEC 60193. It was observed that the model test and CFD results were close to each other, especially at the best efficiency point. The maximum turbine hydraulic efficiency, which was calculated as 94.95% as a result of CFD analysis at the nominal head, was calculated as 95.19% by the model test. The x-blade shape created in the redesigned turbine runner blades ensured homogeneous pressure distribution and increased the hydraulic efficiency significantly.
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