This paper investigates a unmanned aerial vehicle(UAV)deployment problem in a non-orthogonal multiple access(NOMA)system,where the UAV is deployed as an aerial mobile base station to transmit data to two ground users....This paper investigates a unmanned aerial vehicle(UAV)deployment problem in a non-orthogonal multiple access(NOMA)system,where the UAV is deployed as an aerial mobile base station to transmit data to two ground users.An optimization problem is formulated by deploying the UAV for maximizing the sum rate of the two users.In order to solve the optimization problem,the feasible solution region is first reduced to a line segment between two users.Then,the optimization problem is simplified to a univariate problem,which can be solved by derivation under a certain situation,and the corresponding analytical solution is also provided.Moreover,a generalized algorithm,which considers 2 situations,is proposed to further determine the optimal UAV’s location.Specifically,four cases are discussed in the first situation.Extensive simulations are depicted to demonstrate effectiveness of the proposed algorithm and its superiority over the benchmarks in maximizing the two users’sum rate.展开更多
针对大规模电动汽车(EV)随机接入电网时,电动汽车无序充电将会导致电网用电量增加,负荷峰谷差值变大,如何有效降低电动汽车带来的用电负荷风险是未来关注的重点。文中提出了基于车网互动(vehicle to grid,V2G)的电动汽车充放电双层优化...针对大规模电动汽车(EV)随机接入电网时,电动汽车无序充电将会导致电网用电量增加,负荷峰谷差值变大,如何有效降低电动汽车带来的用电负荷风险是未来关注的重点。文中提出了基于车网互动(vehicle to grid,V2G)的电动汽车充放电双层优化调度策略。其中,上层模型以电网总负荷方差最小和代理商调度计划偏差最小为目标函数;下层模型以用户参与调度意愿和调度能力为基础,在代理商配合调度中心计划的前提下,注重提高用户参与度和用户收益最大化。采用多种群遗传算法对模型进行分析,结果表明,所建模型不仅能够很好的平抑电网负荷波动,有效降低负荷峰谷差,并使参与V2G服务的用户经济收益最大化。展开更多
基金the National Natural Science Foundation of China(No.61702258,61901211)the Natural Science Foundation of Jiangsu Province(No.BK20170766).
文摘This paper investigates a unmanned aerial vehicle(UAV)deployment problem in a non-orthogonal multiple access(NOMA)system,where the UAV is deployed as an aerial mobile base station to transmit data to two ground users.An optimization problem is formulated by deploying the UAV for maximizing the sum rate of the two users.In order to solve the optimization problem,the feasible solution region is first reduced to a line segment between two users.Then,the optimization problem is simplified to a univariate problem,which can be solved by derivation under a certain situation,and the corresponding analytical solution is also provided.Moreover,a generalized algorithm,which considers 2 situations,is proposed to further determine the optimal UAV’s location.Specifically,four cases are discussed in the first situation.Extensive simulations are depicted to demonstrate effectiveness of the proposed algorithm and its superiority over the benchmarks in maximizing the two users’sum rate.
文摘针对大规模电动汽车(EV)随机接入电网时,电动汽车无序充电将会导致电网用电量增加,负荷峰谷差值变大,如何有效降低电动汽车带来的用电负荷风险是未来关注的重点。文中提出了基于车网互动(vehicle to grid,V2G)的电动汽车充放电双层优化调度策略。其中,上层模型以电网总负荷方差最小和代理商调度计划偏差最小为目标函数;下层模型以用户参与调度意愿和调度能力为基础,在代理商配合调度中心计划的前提下,注重提高用户参与度和用户收益最大化。采用多种群遗传算法对模型进行分析,结果表明,所建模型不仅能够很好的平抑电网负荷波动,有效降低负荷峰谷差,并使参与V2G服务的用户经济收益最大化。
