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Contract and Lyapunov Optimization-Based Load Scheduling and Energy Management for UAV Charging Stations

机译:合同和Lyapunov优化的无UAV充电站的负载调度和能源管理

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摘要

Nowadays, a large number of civilian unmanned aerial vehicles (UAVs) are increasingly being used in many of our daily applications. However, there are many kinds of UAVs that need to enhance their endurance due to their limited resources. In order to make the UAVs operate efficiently, it is necessary to schedule UAVs with charging requirements. In this paper, renewable energy production and storage equipment on the basis of traditional charging stations is adopted to reduce the power purchase from the distribution network as much as possible. An online algorithm based on Lyapunov optimization is proposed to schedule the charging of UAVs and the energy management of the charging station. Meanwhile, contract theory is used to design the optimal charging strategy in the case of information asymmetry. Hence, local renewable energy can be utilized to the greatest extent, and electricity purchase costs can be reduced. Through the incentive system, users can spontaneously charge at low peak times and avoid the risk of grid overload and high energy cost. The simulation results show that the algorithm can improve the efficiency of charging station operators, allowing users to avoid charging at peak times, and only use real-time information to schedule UAVs. Compared to other algorithms, the proposed scheme can bring good revenue to operators while ensuring long-lasting operations of charging stations.
机译:如今,越来越多地被许多我们日常应用中使用了大量的民用无人驾驶飞行器(UAV)的。不过,也有由于其有限资源的多种需要,以提高自己的耐力无人机。为了使无人机有效地运作,这是必要的充电需求来安排无人机。在本文中,传统的充电站的基础上,可再生能源的生产和存储设备中采用,以减少配电网的电力购买尽可能多地。基于Lyapunov优化的在线算法调度无人机的充电和充电站的能源管理。同时,契约理论来设计最佳的在信息不对称的情况下,充电策略。因此,本地的可再生能源可用于最大程度,和购电成本可以降低。通过激励系统,用户可以自行充电,在低峰时间和避免电网过载和高能源成本的风险。仿真结果表明,该算法能提高充电站运营商,使用户避免在高峰时间充电效率,并且只使用实时信息来安排无人机。相比其他算法,该算法可以带来良好的收入,运营商,同时确保充电站的长效运营。

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