Optimization of Francis turbine runner based on analytic hierarchy process – entropy weight method and multi-objective Lichtenberg algorithm
In multi-energy complementary systems, the inherent randomness and volatility of renewable energy generation necessitate hydropower units with rapid start-up and flexible regulation capabilities to operate as energy-regulation units, ensuring grid stability and effective renewable energy integration...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Engineering Applications of Computational Fluid Mechanics |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/19942060.2025.2541680 |
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| author | Xiaobo Zheng Wei Wang Yaping Zhao Hao Liang Pengcheng Guo Zhihua Li |
| author_facet | Xiaobo Zheng Wei Wang Yaping Zhao Hao Liang Pengcheng Guo Zhihua Li |
| author_sort | Xiaobo Zheng |
| collection | DOAJ |
| description | In multi-energy complementary systems, the inherent randomness and volatility of renewable energy generation necessitate hydropower units with rapid start-up and flexible regulation capabilities to operate as energy-regulation units, ensuring grid stability and effective renewable energy integration. Consequently, hydraulic turbines are compelled to operate for prolonged periods in low-load regions characterized by low efficiency, severe cavitation, and intense vibrations, which significantly jeopardize operational safety and stability. To address these issues, this study develops a multi-condition, multi-objective optimization platform for a Francis turbine runner based on the Analytic Hierarchy Process-Entropy Weight (AHP) method and the Multi-Objective Lichtenberg Algorithm (MOLA). Bézier curves parameterize the runner blades, whereas the AHP-Entropy Weight method determines the optimal weight coefficients for operating conditions across the full load range (20%–100%Pr). The optimization objectives combine weighted efficiency across all conditions and weighted minimum pressure values with MOLA implementing multi-objective design optimization. The results demonstrate that the optimized runner reduces the high-entropy production zones in both the runner and draft tube, thereby lowering the energy losses and enhancing the efficiency throughout the full load range. Specifically, the turbine efficiency increased by 5.4% at 20% Pr and by 2.83% at 50% Pr. The optimized blade geometry significantly shrinks the low-pressure regions, thus improving cavitation resistance. Furthermore, passage vortices, flow separation vortices, and draft tube vortex rope under low-load conditions are effectively suppressed, reducing the pressure pulsation amplitudes by 85% at 0.20fn (20% Pr) and 32% at 0.20fn (50% Pr) while maintaining the rated-load performance. These findings provide critical insights for optimizing the turbine stability and runner design in multi-energy complementary systems. |
| format | Article |
| id | doaj-art-c44564c8a31646db839a5dcc5c21f0c8 |
| institution | Kabale University |
| issn | 1994-2060 1997-003X |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Engineering Applications of Computational Fluid Mechanics |
| spelling | doaj-art-c44564c8a31646db839a5dcc5c21f0c82025-08-20T03:40:46ZengTaylor & Francis GroupEngineering Applications of Computational Fluid Mechanics1994-20601997-003X2025-12-0119110.1080/19942060.2025.2541680Optimization of Francis turbine runner based on analytic hierarchy process – entropy weight method and multi-objective Lichtenberg algorithmXiaobo Zheng0Wei Wang1Yaping Zhao2Hao Liang3Pengcheng Guo4Zhihua Li5College of Water Conservancy and Hydropower Engineering, Xi'an University of Technology, Xi'an, People’s Republic of ChinaCollege of Water Conservancy and Hydropower Engineering, Xi'an University of Technology, Xi'an, People’s Republic of ChinaCollege of Water Conservancy and Hydropower Engineering, Xi'an University of Technology, Xi'an, People’s Republic of ChinaCollege of Water Conservancy and Hydropower Engineering, Xi'an University of Technology, Xi'an, People’s Republic of ChinaCollege of Water Conservancy and Hydropower Engineering, Xi'an University of Technology, Xi'an, People’s Republic of ChinaXi'an Thermal Power Research Institute Co., Ltd., Xi'an, People’s Republic of ChinaIn multi-energy complementary systems, the inherent randomness and volatility of renewable energy generation necessitate hydropower units with rapid start-up and flexible regulation capabilities to operate as energy-regulation units, ensuring grid stability and effective renewable energy integration. Consequently, hydraulic turbines are compelled to operate for prolonged periods in low-load regions characterized by low efficiency, severe cavitation, and intense vibrations, which significantly jeopardize operational safety and stability. To address these issues, this study develops a multi-condition, multi-objective optimization platform for a Francis turbine runner based on the Analytic Hierarchy Process-Entropy Weight (AHP) method and the Multi-Objective Lichtenberg Algorithm (MOLA). Bézier curves parameterize the runner blades, whereas the AHP-Entropy Weight method determines the optimal weight coefficients for operating conditions across the full load range (20%–100%Pr). The optimization objectives combine weighted efficiency across all conditions and weighted minimum pressure values with MOLA implementing multi-objective design optimization. The results demonstrate that the optimized runner reduces the high-entropy production zones in both the runner and draft tube, thereby lowering the energy losses and enhancing the efficiency throughout the full load range. Specifically, the turbine efficiency increased by 5.4% at 20% Pr and by 2.83% at 50% Pr. The optimized blade geometry significantly shrinks the low-pressure regions, thus improving cavitation resistance. Furthermore, passage vortices, flow separation vortices, and draft tube vortex rope under low-load conditions are effectively suppressed, reducing the pressure pulsation amplitudes by 85% at 0.20fn (20% Pr) and 32% at 0.20fn (50% Pr) while maintaining the rated-load performance. These findings provide critical insights for optimizing the turbine stability and runner design in multi-energy complementary systems.https://www.tandfonline.com/doi/10.1080/19942060.2025.2541680Adjustable energy turbineAHP-Entropy weight methodMOLA algorithmvortex distributionentropy production distribution |
| spellingShingle | Xiaobo Zheng Wei Wang Yaping Zhao Hao Liang Pengcheng Guo Zhihua Li Optimization of Francis turbine runner based on analytic hierarchy process – entropy weight method and multi-objective Lichtenberg algorithm Engineering Applications of Computational Fluid Mechanics Adjustable energy turbine AHP-Entropy weight method MOLA algorithm vortex distribution entropy production distribution |
| title | Optimization of Francis turbine runner based on analytic hierarchy process – entropy weight method and multi-objective Lichtenberg algorithm |
| title_full | Optimization of Francis turbine runner based on analytic hierarchy process – entropy weight method and multi-objective Lichtenberg algorithm |
| title_fullStr | Optimization of Francis turbine runner based on analytic hierarchy process – entropy weight method and multi-objective Lichtenberg algorithm |
| title_full_unstemmed | Optimization of Francis turbine runner based on analytic hierarchy process – entropy weight method and multi-objective Lichtenberg algorithm |
| title_short | Optimization of Francis turbine runner based on analytic hierarchy process – entropy weight method and multi-objective Lichtenberg algorithm |
| title_sort | optimization of francis turbine runner based on analytic hierarchy process entropy weight method and multi objective lichtenberg algorithm |
| topic | Adjustable energy turbine AHP-Entropy weight method MOLA algorithm vortex distribution entropy production distribution |
| url | https://www.tandfonline.com/doi/10.1080/19942060.2025.2541680 |
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