Owing to the rapid development of microgrids(MGs)and growing applications of renewable energy resources,multiobjective optimal dispatch of MGs need to be studied in detail.In this study,a multiobjective optimal dispat...Owing to the rapid development of microgrids(MGs)and growing applications of renewable energy resources,multiobjective optimal dispatch of MGs need to be studied in detail.In this study,a multiobjective optimal dispatch model is developed for a standalone MG composed of wind turbines,photovoltaics,diesel engine unit,load,and battery energy storage system.The economic cost,environmental concerns,and power supply consistency are expressed via subobjectives with varying priorities.Then,the analytic hierarchy process algorithm is employed to reasonably specify the weight coefficients of the subobjectives.The quantum particle swarm optimization algorithm is thereafter employed as a solution to achieve optimal dispatch of the MG.Finally,the validity of the proposed model and solution methodology are con firmed by case studies.This study provides refere nee for mathematical model of multiojective optimizati on of MG and can be widely used in current research field.展开更多
This paper introduces the quantum control of Lyapunov functions based on the state distance, the mean of imaginary quantities and state errors.In this paper, the specific control laws under the three forms are given.S...This paper introduces the quantum control of Lyapunov functions based on the state distance, the mean of imaginary quantities and state errors.In this paper, the specific control laws under the three forms are given.Stability is analyzed by the La Salle invariance principle and the numerical simulation is carried out in a 2D test system.The calculation process for the Lyapunov function is based on a combination of the average of virtual mechanical quantities, the particle swarm algorithm and a simulated annealing algorithm.Finally, a unified form of the control laws under the three forms is given.展开更多
提出了一种基于量子粒子群算法(QPSO)的智能天线声阵列自适应波束形成算法模型,该模型应用QPSO对阵列天线半径和阵元初始相位进行调整,进而控制智能天线声阵列的波束形成,使天线波束主瓣对准期望声源信号方向,零陷对准干扰信号方向,并...提出了一种基于量子粒子群算法(QPSO)的智能天线声阵列自适应波束形成算法模型,该模型应用QPSO对阵列天线半径和阵元初始相位进行调整,进而控制智能天线声阵列的波束形成,使天线波束主瓣对准期望声源信号方向,零陷对准干扰信号方向,并形成最优的增益主瓣和旁瓣的峰峰比.Matlab仿真结果表明,该模型增强主瓣方向增益约10 d B,降低噪声方向增益约3.75 d B,有效提升了系统通信能力和抗干扰能力,并且在扫描角度上呈现普适性.展开更多
基金State Grid Corporation Science and Technology Project(520605190010).
文摘Owing to the rapid development of microgrids(MGs)and growing applications of renewable energy resources,multiobjective optimal dispatch of MGs need to be studied in detail.In this study,a multiobjective optimal dispatch model is developed for a standalone MG composed of wind turbines,photovoltaics,diesel engine unit,load,and battery energy storage system.The economic cost,environmental concerns,and power supply consistency are expressed via subobjectives with varying priorities.Then,the analytic hierarchy process algorithm is employed to reasonably specify the weight coefficients of the subobjectives.The quantum particle swarm optimization algorithm is thereafter employed as a solution to achieve optimal dispatch of the MG.Finally,the validity of the proposed model and solution methodology are con firmed by case studies.This study provides refere nee for mathematical model of multiojective optimizati on of MG and can be widely used in current research field.
基金Project supported by the National Natural Science Foundation of China (Grant No.62176140)。
文摘This paper introduces the quantum control of Lyapunov functions based on the state distance, the mean of imaginary quantities and state errors.In this paper, the specific control laws under the three forms are given.Stability is analyzed by the La Salle invariance principle and the numerical simulation is carried out in a 2D test system.The calculation process for the Lyapunov function is based on a combination of the average of virtual mechanical quantities, the particle swarm algorithm and a simulated annealing algorithm.Finally, a unified form of the control laws under the three forms is given.
文摘提出了一种基于量子粒子群算法(QPSO)的智能天线声阵列自适应波束形成算法模型,该模型应用QPSO对阵列天线半径和阵元初始相位进行调整,进而控制智能天线声阵列的波束形成,使天线波束主瓣对准期望声源信号方向,零陷对准干扰信号方向,并形成最优的增益主瓣和旁瓣的峰峰比.Matlab仿真结果表明,该模型增强主瓣方向增益约10 d B,降低噪声方向增益约3.75 d B,有效提升了系统通信能力和抗干扰能力,并且在扫描角度上呈现普适性.
