软基水闸底板脱空是水闸在长期服役期间受水流侵蚀等环境因素影响所产生的一种危害极大且难以察觉的病害。由于其病害部位于水下,传统方法难以检测,该研究提出一种基于高斯过程回归(Gaussian process regression,GPR)代理模型和遗传-自...软基水闸底板脱空是水闸在长期服役期间受水流侵蚀等环境因素影响所产生的一种危害极大且难以察觉的病害。由于其病害部位于水下,传统方法难以检测,该研究提出一种基于高斯过程回归(Gaussian process regression,GPR)代理模型和遗传-自适应惯性权重粒子群(genetic algorithm-adaptive particle swarm optimization,GA-APSO)混合优化算法的水闸底板脱空动力学反演方法,用于检测软基水闸底板脱空。首先,构建表征软基水闸底板脱空参数和水闸结构模态参数之间非线性关系的GPR代理模型;其次,基于GPR代理模型与水闸实测模态参数建立脱空反演的最优化数学模型,将反演问题转化为目标函数最优化求解问题;最后,为提高算法寻优计算的精度,提出一种GA-APSO混合优化算法对目标函数进行脱空反演计算,并提出一种更合理判断反演脱空区域面积和实际脱空区域面积相对误差的指标—面积不重合度。为验证所提方法性能,以一室内软基水闸物理模型为例,对两种不同脱空工况开展研究分析,结果表明,反演脱空区域面积和模型实际设置脱空区域面积的相对误差分别为8.47%和10.77%,相对误差值较小,证明所提方法能有效反演出水闸底板脱空情况,可成为软基水闸底板脱空反演检测的一种新方法。展开更多
分布式储能具有分散灵活等特点,多分布式储能协同配合可以解决单一储能调节能力差、范围小的问题,可以进一步提高新能源消纳能力。提高新能源利用率。本工作通过建立一个光伏电站、两个分布式储能系统模型,并通过分析光伏电站出力,利用...分布式储能具有分散灵活等特点,多分布式储能协同配合可以解决单一储能调节能力差、范围小的问题,可以进一步提高新能源消纳能力。提高新能源利用率。本工作通过建立一个光伏电站、两个分布式储能系统模型,并通过分析光伏电站出力,利用储能系统跟踪光伏出力的特点建立以分布式储能系统出力最小为目标的目标函数,结合发电系统的功率平衡要求、分布式储能系统的电池能量状态(state of energy,SOE)约束、分布式储能系统功率和容量约束,采用线性递减惯性权重粒子群优化算法,旨在在已有的约束条件下,寻求分布式储能系统的最佳效率。通过仿真分析该方法可以提高光伏消纳能力,减少储能系统动作次数,进一步增加储能系统的寿命。展开更多
Since traditional whale optimization algorithms have slow convergence speed,low accuracy and are easy to fall into local optimal solutions,an improved whale optimization algorithm based on mirror selection(WOA-MS)is p...Since traditional whale optimization algorithms have slow convergence speed,low accuracy and are easy to fall into local optimal solutions,an improved whale optimization algorithm based on mirror selection(WOA-MS)is proposed. Specific improvements includes:(1)An adaptive nonlinear inertia weight based on Branin function was introduced to balance global search and local mining.(2) A mirror selection method is proposed to improve the individual quality and speed up the convergence. By optimizing several test functions and comparing the experimental results with other three algorithms,this study verifies that WOA-MS has an excellent optimization performance.展开更多
文摘分布式储能具有分散灵活等特点,多分布式储能协同配合可以解决单一储能调节能力差、范围小的问题,可以进一步提高新能源消纳能力。提高新能源利用率。本工作通过建立一个光伏电站、两个分布式储能系统模型,并通过分析光伏电站出力,利用储能系统跟踪光伏出力的特点建立以分布式储能系统出力最小为目标的目标函数,结合发电系统的功率平衡要求、分布式储能系统的电池能量状态(state of energy,SOE)约束、分布式储能系统功率和容量约束,采用线性递减惯性权重粒子群优化算法,旨在在已有的约束条件下,寻求分布式储能系统的最佳效率。通过仿真分析该方法可以提高光伏消纳能力,减少储能系统动作次数,进一步增加储能系统的寿命。
基金supported by the Natural Science Foundation of Jiangsu Province (No. BK20151479)the Open Foundation of Graduate Innovation Base in Nanjing University of Aeronautics and Astronautics(No. kfjj20190736)
文摘Since traditional whale optimization algorithms have slow convergence speed,low accuracy and are easy to fall into local optimal solutions,an improved whale optimization algorithm based on mirror selection(WOA-MS)is proposed. Specific improvements includes:(1)An adaptive nonlinear inertia weight based on Branin function was introduced to balance global search and local mining.(2) A mirror selection method is proposed to improve the individual quality and speed up the convergence. By optimizing several test functions and comparing the experimental results with other three algorithms,this study verifies that WOA-MS has an excellent optimization performance.
