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Optimization of hydraulic parameters for pipeline system of hydropower station with super long headrace tunnel based on mayfly algorithm considering operational scenarios.
- Source :
- Energy Science & Engineering; Jun2024, Vol. 12 Issue 6, p2341-2364, 24p
- Publication Year :
- 2024
-
Abstract
- This paper studies the optimization of hydraulic parameters for pipeline system of hydropower station with super long headrace tunnel (HSSLHT) based on mayfly algorithm considering operational scenarios. Firstly, the state equation of HSSLHT under load disturbance is derived. The optimization design of hydraulic parameters for pipeline system based on mayfly algorithm is proposed. Then, the optimization of hydraulic parameters is conducted and analyzed. Finally, the effects of pipeline diameters and transfer coefficients of turbines on the optimization of hydraulic parameters for pipeline systems are revealed. The results show that the optimization of hydraulic parameters for pipeline system is a multiobjective problem, and the several objective functions exhibit significant conflicts. Compared to the firefly algorithm and genetic algorithm, the objective function under mayfly algorithm is improved by 14.7% and 5.1%, respectively. The mayfly algorithm can make the hydraulic parameters for the pipeline system reach the Pareto optimal solution under both load decrease condition and load increase condition. The diameter of penstock has an obvious influence on the robustness of dynamic performance of HSSLHT. When the diameter of penstock increases by 30%, the robustness of HSSLHT becomes worse and the robustness index deteriorates by 57%. The reason is that the flow inertia of penstock becomes smaller with the increase of diameter, and the flow inertia of penstock is favorable for resisting disturbance of HSSLHT. The coefficient of throttled orifice head loss and the lengths and head losses of headrace tunnel and penstock are the key hydraulic parameters for matching the operation of HSSLHT. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20500505
- Volume :
- 12
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- Energy Science & Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 178071781
- Full Text :
- https://doi.org/10.1002/ese3.1726