4.7 Article

Sponge Supercapacitor rule-based energy management strategy for wireless sensor nodes optimized by using dynamic programing algorithm

期刊

ENERGY
卷 239, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2021.122368

关键词

Hybrid energy storage system; Energy management strategy; Dynamic programming; Sponge supercapacitor; Wireless sensor networks

资金

  1. Tsinghua University-China Mobile Communications Group Co., Ltd. Joint Institute
  2. Beijing Innovation Center for Future Chips

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This study proposes a sponge supercapacitor-based energy management strategy, which utilizes dynamic programming for global optimization. Compared with traditional strategies, this proposed strategy achieves significant improvements and can extend the lifetime of solar-powered wireless sensor network nodes.
Hybrid energy storage systems composed of batteries and supercapacitors (SCs) can provide a stable and sustainable power source for wireless sensor network (WSN) nodes, where the energy management strategy (EMS) plays a significant role. However, the design of a traditional EMS is based on empirical rules and cannot fully utilize the SC. In this study, we propose the concept of a sponge SC and design a strategy based on it to prolong the lifetime of solar-powered WSN nodes. This sponge SC EMS is realized by using dynamic programming (DP), which is a global optimization algorithm. Thus, the proposed EMS is significantly improved over other traditional empirical-based strategies. The difference between the lifetime simulated by the proposed strategy and the optimal upper bound given by DP is within 40%, and the novel strategy extends the battery lifetime by 32%-77% compared with the best existing strategies investigated. The robustness of the proposed method is also validated. It can be confirmed that the strategy performs well under different workloads and sunlight conditions. The sponge SC rule-based hybrid EMS provides a theoretical near-optimal solution for the extension of the life of the WSN node, contributing to wider application prospects of the WSN node. (C) 2021 Elsevier Ltd. All rights reserved.

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