The hazardous effects of pollutants from conventional fuel vehicles have caused the scientific world to move towards environmentally friendly energy sources. Though we have various renewable energy sources, the perfect one to use as an energy source for vehicles is hydrogen. Like electricity, hydrogen is an energy carrier that has the ability to deliver incredible amounts of energy. Onboard hydrogen storage in vehicles is an important factor that should be considered when designing fuel cell vehicles. In this study, a recent development in hydrogen fuel cell engines is reviewed to scrutinize the feasibility of using hydrogen as a major fuel in transportation systems. A fuel cell is an electrochemical device that can produce electricity by allowing chemical gases and oxidants as reactants. With anodes and electrolytes, the fuel cell splits the cation and the anion in the reactant to produce electricity. Fuel cells use reactants, which are not harmful to the environment and produce water as a product of the chemical reaction. As hydrogen is one of the most efficient energy carriers, the fuel cell can produce direct current (DC) power to run the electric car. By integrating a hydrogen fuel cell with batteries and the control system with strategies, one can produce a sustainable hybrid car.
This paper presents a method for multidisciplinary design optimization of offshore wind turbines at system level. The formulation and implementation that enable the integrated aerodynamic and structural design of the rotor and tower simultaneously are detailed. The objective function to be minimized is the levelized cost of energy. The model includes various design constraints: stresses, deflections, modal frequencies and fatigue limits along different stations of the blade and tower. The rotor design variables are: chord and twist distribution, blade length, rated rotational speed and structural thicknesses along the span. The tower design variables are: tower thickness and diameter distribution, as well as the tower height. For the other wind turbine components, a representative mass model is used to include their dynamic interactions in the system. To calculate the system costs, representative cost models of a wind turbine located in an offshore wind farm are used. To show the potential of the method and to verify its usefulness, the 5 MW NREL wind turbine is used as a case study. The result of the design optimization process shows 2.3% decrease in the levelized cost of energy for a representative Dutch site, while satisfying all the design constraints.
Computational fluid dynamics (CFD) is increasingly used to analyze wind turbines, and the next logical step is to develop CFD‐based optimization to enable further gains in performance and reduce model uncertainties. We present an aerodynamic shape optimization framework consisting of a Reynolds‐averaged Navier Stokes solver coupled to a numerical optimization algorithm, a geometry modeler, and a mesh perturbation algorithm. To efficiently handle the large number of design variables, we use a gradient‐based optimization technique together with an adjoint method for computing the gradients of the torque coefficient with respect to the design variables. To demonstrate the effectiveness of the proposed approach, we maximize the torque of the NREL VI wind turbine blade with respect to pitch, twist, and airfoil shape design variables while constraining the blade thickness. We present a series of optimization cases with increasing number of variables, both for a single wind speed and for multiple wind speeds. For the optimization at a single wind speed performed with respect to all the design variables (1 pitch, 11 twist, and 240 airfoil shape variables), the torque coefficient increased by 22.4% relative to the NREL VI design. For the multiple‐speed optimization, the torque increased by an average of 22.1%. Depending on the CFD mesh size and number of design variables, the optimization time ranges from 2 to 24h when using 256 cores, which means that wind turbine designers can use this process routinely. Copyright © 2016 John Wiley & Sons, Ltd.
a b s t r a c tWind energy has experienced a continuous cost reduction in the last decades. A popular cost reduction technique is to increase the rated power of the wind turbine by making it larger. However, it is not clear whether further upscaling of the existing wind turbines beyond the 5-7 MW range is technically feasible and economically attractive. To address this question, this study uses 5, 10, and 20 MW wind turbines that are developed using multidisciplinary design optimization as upscaling data points. These wind turbines are upwind, 3-bladed, pitch-regulated, variable-speed machines with a tubular tower. Based on the design data and properties of these wind turbines, scaling trends such as loading, mass, and cost are developed. These trends are used to study the technical and economical aspects of upscaling and its impact on the design and cost. The results of this research show the technical feasibility of the existing wind turbines up to 20 MW, but the design of such an upscaled machine is cost prohibitive. Mass increase of the rotor is identified as a main design challenge to overcome. The results of this research support the development of alternative lightweight materials and design concepts such as a two-bladed downwind design for upscaling to remain a cost effective solution for future wind turbines.
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