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Operation policies for Energy Harvesting Devices with imperfect State-of-Charge knowledge

机译:充电状态知识不完善的能量收集设备的操作策略

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As Energy Harvesting Devices (EHD) become more widely deployed in sensor network platforms, the need arises for 'smart' operation policies which can ensure long-term, autonomous and reliable operation. Existing research has relied on the implicit assumption of perfect knowledge of the energy available in the EHD. However, estimating the energy level of the batteries or super-capacitors employed in real-world EHDs, commonly known as State-Of-Charge (SOC), is a non-trivial task. In this paper, we design operation policies that maximize the long-term reward under imperfect knowledge of the SOC. Through an array of simulation results, we quantify the performance degradation due to imperfect SOC knowledge, and show that it increases with decreasing storage capacity and increasing variance in the energy arrival process. In the particular case of a two-state controller, i.e., a controller which knows only if the SOC is HIGH or LOW, we prove that, for a linear reward function, there is no performance loss, while, for a logarithmic reward function, simulations show that the loss is typically less than 5%.
机译:随着能量收集设备(EHD)越来越广泛地部署在传感器网络平台中,对“智能”操作策略的需求不断增加,这些策略可以确保长期,自主和可靠的操作。现有研究依赖于对EHD中可用能量的完备知识的隐含假设。但是,估算通常用于充电状态(SOC)的实际EHD中所使用的电池或超级电容器的能量水平并非易事。在本文中,我们设计了在SOC知识不完善的情况下最大化长期回报的运营策略。通过一系列仿真结果,我们量化了由于不完善的SOC知识而导致的性能下降,并表明随着存储容量的减少和能量到达过程中方差的增加,性能下降的趋势也越来越大。在二态控制器的特定情况下,即仅知道SOC是HIGH还是LOW的控制器,我们证明对于线性奖励函数,没有性能损失,而对于对数奖励函数,仿真表明,损耗通常小于5%。

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