Transformations of Steiner tree problem variants have been frequently discussed in the literature. Besides allowing to easily transfer complexity results, they constitute a central pillar of exact state-of-the-art sol...Transformations of Steiner tree problem variants have been frequently discussed in the literature. Besides allowing to easily transfer complexity results, they constitute a central pillar of exact state-of-the-art solvers for well-known variants such as the Steiner tree problem in graphs. In this article transformations for both the prize-collecting Steiner tree problem and the maximum-weight connected subgraph problem to the Steiner arborescence problem are introduced for the first time. Furthermore, the considerable implications for practical solving approaches will be demonstrated, including the computation of strong upper and lower bounds.展开更多
光伏系统在局部遮阴条件下,系统输出功率呈现多峰值现象,使用传统的最大功率追踪(maximum power point tracking,MPPT)方法对其进行追踪时存在追踪精度低的缺点。针对该问题提出一种改进粒子群算法的MPPT方法。该方法使用拉丁超立方抽...光伏系统在局部遮阴条件下,系统输出功率呈现多峰值现象,使用传统的最大功率追踪(maximum power point tracking,MPPT)方法对其进行追踪时存在追踪精度低的缺点。针对该问题提出一种改进粒子群算法的MPPT方法。该方法使用拉丁超立方抽样初始化种群代替粒子群算法中随机初始化种群,保证初始化的种群更加均匀。同时使用自适应权重代替固定权重,更好地平衡粒子群的探索和开发能力,避免算法过早地陷入局部最优解。在Matlab/Simulink中搭建光伏系统MPPT仿真模型,通过均匀光照、静态遮阴光照和动态遮阴光照3种情况下的仿真对比,所提的改进粒子群优化算法比扰动观察法和粒子群优化算法有更好的追踪精度,验证所提算法在光伏MPPT控制中的有效性。展开更多
文摘Transformations of Steiner tree problem variants have been frequently discussed in the literature. Besides allowing to easily transfer complexity results, they constitute a central pillar of exact state-of-the-art solvers for well-known variants such as the Steiner tree problem in graphs. In this article transformations for both the prize-collecting Steiner tree problem and the maximum-weight connected subgraph problem to the Steiner arborescence problem are introduced for the first time. Furthermore, the considerable implications for practical solving approaches will be demonstrated, including the computation of strong upper and lower bounds.
文摘光伏系统在局部遮阴条件下,系统输出功率呈现多峰值现象,使用传统的最大功率追踪(maximum power point tracking,MPPT)方法对其进行追踪时存在追踪精度低的缺点。针对该问题提出一种改进粒子群算法的MPPT方法。该方法使用拉丁超立方抽样初始化种群代替粒子群算法中随机初始化种群,保证初始化的种群更加均匀。同时使用自适应权重代替固定权重,更好地平衡粒子群的探索和开发能力,避免算法过早地陷入局部最优解。在Matlab/Simulink中搭建光伏系统MPPT仿真模型,通过均匀光照、静态遮阴光照和动态遮阴光照3种情况下的仿真对比,所提的改进粒子群优化算法比扰动观察法和粒子群优化算法有更好的追踪精度,验证所提算法在光伏MPPT控制中的有效性。
