Unmanned aerial vehicles(UAVs) are advantageous for data collection in wireless sensor networks(WSNs) due to its low cost of use,flexible deployment,controllable mobility,etc. However,how to cope with the inherent iss...Unmanned aerial vehicles(UAVs) are advantageous for data collection in wireless sensor networks(WSNs) due to its low cost of use,flexible deployment,controllable mobility,etc. However,how to cope with the inherent issues of energy limitation and data security in the WSNs is challenging in such an application paradigm. To this end,based on the framework of physical layer security,an optimization problem for maximizing secrecy energy efficiency(EE) of data collection is formulated,which focuses on optimizing the UAV’s positions and the sensors’ transmit power. To overcome the difficulties in solving the optimization problem,the methods of fractional programming and successive convex approximation are then adopted to gradually transform the original problem into a series of tractable subproblems which are solved in an iterative manner. As shown in simulation results,by the joint designs in the spatial domain of UAV and the power domain of sensors,the proposed algorithm achieves a significant improvement of secrecy EE and rate.展开更多
在电网储能领域,获取储能系统负荷功率合理分配方案的关键是优化求解算法,若求解算法选择不合理或算法本身存在缺陷,求解过程会过于早熟,仅得到局部最优解而非全局最优解。为解决这一问题,提出一种微电网分布式储能系统负荷功率的动态...在电网储能领域,获取储能系统负荷功率合理分配方案的关键是优化求解算法,若求解算法选择不合理或算法本身存在缺陷,求解过程会过于早熟,仅得到局部最优解而非全局最优解。为解决这一问题,提出一种微电网分布式储能系统负荷功率的动态分配方法。该方法先进行微电网分布式储能系统运行数据的采集;然后考虑负荷功率平均损耗率、荷电状态(state of charge,SOC)平衡系数,设置一个分布式储能系统多目标分配函数;最后在SOC、充放电量、充放电流这3个约束条件限制下,利用改进麻雀搜索算法求取多目标函数最优解,得出微电网分布式储能系统负荷功率的最优动态分配方案。结果表明:应用所提方法,负荷功率平均损耗相对更低,SOC平衡系数相对更高,多目标函数值相对更小。说明该分配方案更为科学、合理,更能保证储能系统的平稳运行,实现系统高质量供电。展开更多
基金Supported by the National Natural Science Foundation of China(No.61871401).
文摘Unmanned aerial vehicles(UAVs) are advantageous for data collection in wireless sensor networks(WSNs) due to its low cost of use,flexible deployment,controllable mobility,etc. However,how to cope with the inherent issues of energy limitation and data security in the WSNs is challenging in such an application paradigm. To this end,based on the framework of physical layer security,an optimization problem for maximizing secrecy energy efficiency(EE) of data collection is formulated,which focuses on optimizing the UAV’s positions and the sensors’ transmit power. To overcome the difficulties in solving the optimization problem,the methods of fractional programming and successive convex approximation are then adopted to gradually transform the original problem into a series of tractable subproblems which are solved in an iterative manner. As shown in simulation results,by the joint designs in the spatial domain of UAV and the power domain of sensors,the proposed algorithm achieves a significant improvement of secrecy EE and rate.
文摘在电网储能领域,获取储能系统负荷功率合理分配方案的关键是优化求解算法,若求解算法选择不合理或算法本身存在缺陷,求解过程会过于早熟,仅得到局部最优解而非全局最优解。为解决这一问题,提出一种微电网分布式储能系统负荷功率的动态分配方法。该方法先进行微电网分布式储能系统运行数据的采集;然后考虑负荷功率平均损耗率、荷电状态(state of charge,SOC)平衡系数,设置一个分布式储能系统多目标分配函数;最后在SOC、充放电量、充放电流这3个约束条件限制下,利用改进麻雀搜索算法求取多目标函数最优解,得出微电网分布式储能系统负荷功率的最优动态分配方案。结果表明:应用所提方法,负荷功率平均损耗相对更低,SOC平衡系数相对更高,多目标函数值相对更小。说明该分配方案更为科学、合理,更能保证储能系统的平稳运行,实现系统高质量供电。
