We study the parameter estimation of a nonlinear chaotic system,which can be essentially formulated as a multidimensional optimization problem.In this paper,an orthogonal learning cuckoo search algorithm is used to es...We study the parameter estimation of a nonlinear chaotic system,which can be essentially formulated as a multidimensional optimization problem.In this paper,an orthogonal learning cuckoo search algorithm is used to estimate the parameters of chaotic systems.This algorithm can combine the stochastic exploration of the cuckoo search and the exploitation capability of the orthogonal learning strategy.Experiments are conducted on the Lorenz system and the Chen system.The proposed algorithm is used to estimate the parameters for these two systems.Simulation results and comparisons demonstrate that the proposed algorithm is better or at least comparable to the particle swarm optimization and the genetic algorithm when considering the quality of the solutions obtained.展开更多
Along with the increasing integration of renewable energy generation in AC-DC power networks,investigating the dynamic behaviors of this complex system with a proper equivalent model is significant.This paper presents...Along with the increasing integration of renewable energy generation in AC-DC power networks,investigating the dynamic behaviors of this complex system with a proper equivalent model is significant.This paper presents an equivalent modeling method for the AC-DC power networks with doubly-fed induction generator(DFIG)based wind farms to decrease the simulation scale and computational burden.For the AC-DC power networks,the equivalent modeling strategy in accordance with the physical structure simplification is stated.Regarding the DFIG-based wind farms,the equivalent modeling based on the sequential identification of multi-machine parameters using the improved chaotic cuckoo search algorithm(ICCSA)is conducted.In light of the MATLAB simulation platform,a two-zone four-DC interconnected power grid with wind farms is built to check the efficacy of the proposed equivalentmodelingmethod.Fromthe simulation analyses and comparative validation in different algorithms and cases,the proposed method can precisely reflect the steady and dynamic performance of the demonstrated system under N-1 and N-2 fault scenarios,and it can efficiently achieve the parameter identification of the wind farms and fulfill the equivalent modeling.Consequently,the proposed approach’s effectiveness and suitability are confirmed.展开更多
针对麻雀搜索算法收敛速度慢、精确度不高、易陷入局部最优等问题,文中提出了一种融合多策略改进的麻雀搜索算法(improved sparrow search algorithm based on multiple strategies,ISSAMS)。通过引入Circle混沌映射初始化种群,增加种...针对麻雀搜索算法收敛速度慢、精确度不高、易陷入局部最优等问题,文中提出了一种融合多策略改进的麻雀搜索算法(improved sparrow search algorithm based on multiple strategies,ISSAMS)。通过引入Circle混沌映射初始化种群,增加种群的多样性,提高全局搜索能力;利用正余弦搜索策略,更新发现者的位置,选择最佳位置,增强局部搜索能力,避免陷入全局最优;加入萤火虫扰动更新最优个体位置,寻找可行解,提高局部搜索能力和寻优速度。为了验证算法改进的有效性,选取5个基准函数进行仿真实验,其中3个基准函数为单峰函数,2个为多峰函数,并与遗传算法、灰狼算法、粒子群算法和麻雀搜索算法比较。通过仿真实验结果表明基于多策略改进后的麻雀搜索算法具备跳出局部最优解能力,收敛速度更快,同时精确度更高,在对比其他4种算法后其总体性能更好。通过将该改进应用到优化BP神经网络的阈值和权值中,对比未改进的麻雀搜索算法优化的BP模型,其误差降低了14.73%,并且与另外3种算法优化的BP模型对比,其基于多策略改进的麻雀搜索算法优化模型的平均绝对百分比误差是最低的,效果最好,进一步验证了该改进算法的有效性。展开更多
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 60473042,60573067 and 60803102)
文摘We study the parameter estimation of a nonlinear chaotic system,which can be essentially formulated as a multidimensional optimization problem.In this paper,an orthogonal learning cuckoo search algorithm is used to estimate the parameters of chaotic systems.This algorithm can combine the stochastic exploration of the cuckoo search and the exploitation capability of the orthogonal learning strategy.Experiments are conducted on the Lorenz system and the Chen system.The proposed algorithm is used to estimate the parameters for these two systems.Simulation results and comparisons demonstrate that the proposed algorithm is better or at least comparable to the particle swarm optimization and the genetic algorithm when considering the quality of the solutions obtained.
基金supported by the Science and Technology Project of Central China Branch of State Grid Corporation of China under 5214JS220010.
文摘Along with the increasing integration of renewable energy generation in AC-DC power networks,investigating the dynamic behaviors of this complex system with a proper equivalent model is significant.This paper presents an equivalent modeling method for the AC-DC power networks with doubly-fed induction generator(DFIG)based wind farms to decrease the simulation scale and computational burden.For the AC-DC power networks,the equivalent modeling strategy in accordance with the physical structure simplification is stated.Regarding the DFIG-based wind farms,the equivalent modeling based on the sequential identification of multi-machine parameters using the improved chaotic cuckoo search algorithm(ICCSA)is conducted.In light of the MATLAB simulation platform,a two-zone four-DC interconnected power grid with wind farms is built to check the efficacy of the proposed equivalentmodelingmethod.Fromthe simulation analyses and comparative validation in different algorithms and cases,the proposed method can precisely reflect the steady and dynamic performance of the demonstrated system under N-1 and N-2 fault scenarios,and it can efficiently achieve the parameter identification of the wind farms and fulfill the equivalent modeling.Consequently,the proposed approach’s effectiveness and suitability are confirmed.
文摘针对麻雀搜索算法收敛速度慢、精确度不高、易陷入局部最优等问题,文中提出了一种融合多策略改进的麻雀搜索算法(improved sparrow search algorithm based on multiple strategies,ISSAMS)。通过引入Circle混沌映射初始化种群,增加种群的多样性,提高全局搜索能力;利用正余弦搜索策略,更新发现者的位置,选择最佳位置,增强局部搜索能力,避免陷入全局最优;加入萤火虫扰动更新最优个体位置,寻找可行解,提高局部搜索能力和寻优速度。为了验证算法改进的有效性,选取5个基准函数进行仿真实验,其中3个基准函数为单峰函数,2个为多峰函数,并与遗传算法、灰狼算法、粒子群算法和麻雀搜索算法比较。通过仿真实验结果表明基于多策略改进后的麻雀搜索算法具备跳出局部最优解能力,收敛速度更快,同时精确度更高,在对比其他4种算法后其总体性能更好。通过将该改进应用到优化BP神经网络的阈值和权值中,对比未改进的麻雀搜索算法优化的BP模型,其误差降低了14.73%,并且与另外3种算法优化的BP模型对比,其基于多策略改进的麻雀搜索算法优化模型的平均绝对百分比误差是最低的,效果最好,进一步验证了该改进算法的有效性。
