EmRep: Energy management relying on state-of-charge extrema prediction

IF 1.1 4区计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

IET Computers and Digital Techniques Pub Date : 2021-08-17 DOI:10.1049/cdt2.12033

Lars Hanschke, Christian Renner

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引用次数: 1

Abstract

The persistent rise of Energy Harvesting Wireless Sensor Networks entails increasing demands on the efficiency and configurability of energy management. New applications often profit from or even require user-defined time-varying utilities, for example, the health assessment of bridges is only possible at rushhour. However, monitoring times do not necessarily overlap with energy harvest periods. This misalignment is often corrected by over-provisioning the energy storage. Favourable small-footprint and cheap energy storage, however, fill up quickly and waste surplus energy. Hence, EmRep is presented, which decouples the energy management of high-intake from low-intake harvest periods. Based on the State-of-Charge extrema prediction, the authors enhance energy management and reduce saturation of energy storage by design. Considering multiple user-defined utility profiles, the benefits of EmRep in combination with a variety of prediction algorithms, time resolutions, and energy storage sizes are showcased. EmRep is tailored to platforms with small energy storage, in which it is found that it doubles effective utility, and also increases performance by $10 %$ with large-sized storage.

Abstract Image

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EmRep:基于充电状态极值预测的能源管理

能量收集无线传感器网络的持续发展对能量管理的效率和可配置性提出了越来越高的要求。新的应用程序通常受益于甚至需要用户定义的时变实用程序，例如，只有在高峰时段才能对桥梁进行健康评估。然而，监测时间不一定与能量收集时间重叠。这种偏差通常通过过度配置能量存储来纠正。然而，有利的小足迹和廉价的能源储存很快就会被填满，并浪费多余的能源。因此，提出了EmRep，将高摄入和低摄入收获期的能量管理解耦。基于荷电状态极值预测，通过设计提高储能系统的能量管理，降低储能系统的饱和。考虑到多个用户定义的公用事业配置文件，EmRep与各种预测算法、时间分辨率和能量存储大小相结合的优势得到了展示。EmRep是为小型储能平台量身定制的，在小型储能平台上，它的有效效用翻了一番，在大型储能平台上，它的性能也提高了10%。

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来源期刊

IET Computers and Digital Techniques 工程技术-计算机：理论方法

CiteScore

3.50

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： IET Computers & Digital Techniques publishes technical papers describing recent research and development work in all aspects of digital system-on-chip design and test of electronic and embedded systems, including the development of design automation tools (methodologies, algorithms and architectures). Papers based on the problems associated with the scaling down of CMOS technology are particularly welcome. It is aimed at researchers, engineers and educators in the fields of computer and digital systems design and test. The key subject areas of interest are: Design Methods and Tools: CAD/EDA tools, hardware description languages, high-level and architectural synthesis, hardware/software co-design, platform-based design, 3D stacking and circuit design, system on-chip architectures and IP cores, embedded systems, logic synthesis, low-power design and power optimisation. Simulation, Test and Validation: electrical and timing simulation, simulation based verification, hardware/software co-simulation and validation, mixed-domain technology modelling and simulation, post-silicon validation, power analysis and estimation, interconnect modelling and signal integrity analysis, hardware trust and security, design-for-testability, embedded core testing, system-on-chip testing, on-line testing, automatic test generation and delay testing, low-power testing, reliability, fault modelling and fault tolerance. Processor and System Architectures: many-core systems, general-purpose and application specific processors, computational arithmetic for DSP applications, arithmetic and logic units, cache memories, memory management, co-processors and accelerators, systems and networks on chip, embedded cores, platforms, multiprocessors, distributed systems, communication protocols and low-power issues. Configurable Computing: embedded cores, FPGAs, rapid prototyping, adaptive computing, evolvable and statically and dynamically reconfigurable and reprogrammable systems, reconfigurable hardware. Design for variability, power and aging: design methods for variability, power and aging aware design, memories, FPGAs, IP components, 3D stacking, energy harvesting. Case Studies: emerging applications, applications in industrial designs, and design frameworks.