Optimization, Numerical, and Experimental Study of a Propeller Pump as TurbineMicro hydropower station is one of the clean choices for offgrid points with available hydropotential. The challenging in this type of energy production is the high capital cost of the installed capacity that is worse for low-head micro hydropower stations. Turbine price is the main problem for this type of energy production. In this research, a simple machine has been introduced instead of conventional propeller turbines. The key is using an axial pump as a propeller turbine. In the present research, a propeller pump was simulated as a turbine by numerical methods. Computational fluid dynamics (CED) was adopted in the direct and reverse modes performance prediction of a single propeller pump. To give a more accurate CED result, all domains within the machine control volume were modeled and hexahedral structured mesh was generated during CED simulation. Complete peiformance curves of its pump and turbine modes were acquired. Eor verification of the numerical results, the machine has been tested in an established test ring. The results showed that a propeller pump could be easily run as a low-head turbine. In the next, the goal was to optimize the geometry of the blades of axial turbine runner which leads to maximum hydraulic efficiency by changing the design parameters of camber line in five sections of a blade. The efficiency of the initial geometry was improved by various objective functions and optimized geometry was obtained by genetic algorithm and artificial neural network to find the best efficiency of the turbine. The results showed that the efficiency is improved by more than 14%. Indeed the geometry has better performance in cavitation.
Use of wind turbines is rapidly growing because of environmental impacts and daily increase in energy cost. Therefore, improving the wind turbines' characteristics is an important issue in this regard. This study has two objectives: one is investigating the aerodynamic performance of wind turbine blades and the other is developing an efficient approach for shape optimization of blades. The numerical solver of flow field was validated by phase VI rotor as a case study. First, flow field around the wind turbine blades was simulated using computational flow dynamics (CFD) and blade element momentum (BEM) methods, then obtained results were validated by available experimental data to show an appropriate conformity. Then for yielding the optimal answer, a shape optimization algorithm was used based on artificial bee colony (ABC) coupled by artificial neural networks (ANNs) as an approximate model. Effect of most important parameters in wind turbine, such as twist angle, chord line, and pitch angle, was changed till achieving the best performance. The flow characteristics of optimized and initial geometries were compared. The results of global optimization showed a value of 8.58% increase for output power. By using pitch power regulate, the maximum power was shifted to higher wind speed and results in a steady power for all work points.
Abstract. In our country we have enormous low head potation flows in agricultures and aquacultures with almost fix flow rates that can be used as micro hydro power plants for producing energy. But the main problem is the high capital price per kW. Therefore there is needed to design a simple machine with a good runner for covering the various potential flows. In this paper an axial hydro turbine has designed for some low heads micro potential flow with flow rates ranged from 50 lit/sec to 150 lit/sec and heads ranged from 1 m to 5 m. The initial runner designed using classical methods and then the runner geometry has been optimized by evolutionary optimization algorithms. The final design has been simulated by a commercial flow solver in a various blade positions. The results showed a wide range characteristic curve with a wide range high efficiency.
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