In order to reduce the total resistance of a hull, an optimization framework for the bulbous bow optimization was presented. The total resistance in calm water was selected as the objective function, and the overset m...In order to reduce the total resistance of a hull, an optimization framework for the bulbous bow optimization was presented. The total resistance in calm water was selected as the objective function, and the overset mesh technique was used for mesh generation. RANS method was used to calculate the total resistance of the hull. In order to improve the efficiency and smoothness of the geometric reconstruction, the arbitrary shape deformation （ASD） technique was introduced to change the shape of the bulbous bow. To improve the global search ability of the particle swarm optimization （PSO） algorithm, an improved particle swarm optimization （IPSO） algorithm was proposed to set up the optimization model. After a series of optimization analyses, the optimal hull form was found. It can be concluded that the simulation based design framework built in this paper is a promising method for bulbous bow optimization.展开更多
针对传统的扰动观察法在光伏最大功率点跟踪(Maximum Power Point Tracking,MPPT)控制中存在着响应速度慢,难以在最大功率点保持平稳等问题,提出了一种假设法并对传统的粒子群算法提出一种改变惯性权重、学习因子的自适应粒子群算法来...针对传统的扰动观察法在光伏最大功率点跟踪(Maximum Power Point Tracking,MPPT)控制中存在着响应速度慢,难以在最大功率点保持平稳等问题,提出了一种假设法并对传统的粒子群算法提出一种改变惯性权重、学习因子的自适应粒子群算法来实现全局最大功率点跟踪。假设法主要是通过公式假设出最大功率点,基于最大功率点位置进行步长的改进。IPSO算法主要是调整传统粒子群算法的参数、优化粒子的搜索顺序、减少迭代次数。通过MATLAB/SIMULINK软件对其建模仿真,得到了假设法还有IPSO算法的仿真结果,并与传统的算法作了对比。结果表明,采用假设法还有IPSO算法都能够实现光伏最大功率点跟踪的精确控制,有助于光伏系统最大功率点跟踪技术的快速实现,具有较好的应用前景。展开更多
基金financially supported by the National Natural Science Foundation of China(Grant No.51009087)the National Science Foundation of Shanghai(Grant No.14ZR1419500)
文摘In order to reduce the total resistance of a hull, an optimization framework for the bulbous bow optimization was presented. The total resistance in calm water was selected as the objective function, and the overset mesh technique was used for mesh generation. RANS method was used to calculate the total resistance of the hull. In order to improve the efficiency and smoothness of the geometric reconstruction, the arbitrary shape deformation （ASD） technique was introduced to change the shape of the bulbous bow. To improve the global search ability of the particle swarm optimization （PSO） algorithm, an improved particle swarm optimization （IPSO） algorithm was proposed to set up the optimization model. After a series of optimization analyses, the optimal hull form was found. It can be concluded that the simulation based design framework built in this paper is a promising method for bulbous bow optimization.
文摘针对传统的扰动观察法在光伏最大功率点跟踪(Maximum Power Point Tracking,MPPT)控制中存在着响应速度慢,难以在最大功率点保持平稳等问题,提出了一种假设法并对传统的粒子群算法提出一种改变惯性权重、学习因子的自适应粒子群算法来实现全局最大功率点跟踪。假设法主要是通过公式假设出最大功率点,基于最大功率点位置进行步长的改进。IPSO算法主要是调整传统粒子群算法的参数、优化粒子的搜索顺序、减少迭代次数。通过MATLAB/SIMULINK软件对其建模仿真,得到了假设法还有IPSO算法的仿真结果,并与传统的算法作了对比。结果表明,采用假设法还有IPSO算法都能够实现光伏最大功率点跟踪的精确控制,有助于光伏系统最大功率点跟踪技术的快速实现,具有较好的应用前景。
