文章快速检索 高级检索
 重庆大学学报  2020, Vol. 43 Issue (1): 90-99  DOI: 10.11835/j.issn.1000-582X.2020.01.010 RIS（文献管理工具） 0

### 引用本文

HE Jin, ZHONG Yuanchang, SUN Lili, MA Tianzhi. Energy management strategy of WSNs node based on photovoltaic capacitance[J]. Journal of Chongqing University, 2020, 43(1): 90-99. DOI: 10.11835/j.issn.1000-582X.2020.01.010.

### 文章历史

1. 重庆大学 微电子与通信工程学院, 重庆 400044;
2. 重庆工程职业技术学院 电气工程学院, 重庆 402260

Energy management strategy of WSNs node based on photovoltaic capacitance
HE Jin 1,2, ZHONG Yuanchang 1, SUN Lili 1, MA Tianzhi 1
1. School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, P. R. China;
2. School of Electrical Engineering, Chongqing Vocational Institute of Engineering, Chongqing 402260, P. R. China
Abstract: To solve the problem of the deficiency in energy allocation and management mechanism based on prediction algorithm in WSNs, energy consumption management in solar chargeable wireless sensor networks is studied, and energy neutral management mechanism based on historical capacity is proposed. A node energy acquisition model for adaptive tracking of sunlight is designed and an energy neutral management mechanism based on historical energy acquisition is constructed. According to the available energy converted from solar energy in the current operation cycle, the duty cycle of the node in the next operation cycle is adjusted to solve the optimization problem of node solar energy acquisition and node energy consumption. The experimental results show that the proposed energy neutral management mechanism based on historical energy acquisition achieves the best match between the size of solar panels and energy consumption of nodes, and provides a valuable solution for energy acquisition and energy consumption management in solar chargeable wireless sensor networks.
Keywords: solar rechargeable wireless sensor network    adaptive tracking of sunlight    energy neutral management mechanism

1 自动跟踪太阳能的节点获能模型

 图 1 太阳能可充电传感器节点电池模型 Fig. 1 Solar rechargeable sensor node battery model
2 基于历史获能的能量中性管理机制

 ${T_{oc}} = N{T_{{\rm{slt}}}},$ (1)

 ${E_h}\left( k \right) = \int t + {T_{{\rm{slt}}}}{P_h}\left( k \right){\rm{d}}t,$ (2)

 图 2 节点活动状态时间片构成 Fig. 2 The time slice of nodes active state

 ${T_{{\rm{rc}}}} = \left( {q/p} \right){T_r},$ (3)

 $E_{{\rm{rc}}}^{\left( {m,k} \right)}\left( i \right) = \sum\limits_{l = 1}^u {E_{{\rm{ch}}}^{\left( {l,m,k} \right)}} \left( i \right) + \sum\limits_{j = 1}^{q/p - u} {E_{{\rm{cm}}}^{\left( {j,m,k} \right)}} \left( i \right),$ (4)

 $E_{{\rm{rc}}}^{\left( {m,k} \right)}\left( i \right) \ne E_{{\rm{rc}}}^{\left( {m + 1,k} \right)}\left( i \right),\left( {m = 1,2,3, \cdots } \right),$ (5)

 $E_{{\rm{ctal}}}^k\left( i \right) = \sum\limits_{m = 1}^L {E_{{\rm{rc}}}^{\left( {m,k} \right)}\left( i \right)} ,$ (6)

 $L = \left\{ \begin{array}{l} \left[ {\frac{{\eta {T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}}} \right],\left( {\frac{{\eta {T_{{\rm{slt }}}}}}{{{T_{{\rm{rc}}}}}} - \left[ {\frac{{\eta {T_{{\rm{slt }}}}}}{{{T_{{\rm{rc}}}}}}} \right] < 0.5} \right),\\ \left[ {\frac{{\eta {T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}}} \right] + 1,\left( {\frac{{\eta {T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}} - \left[ {\frac{{\eta {T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}}} \right] \ge 0.5} \right), \end{array} \right.$ (7)

 $E_{{\rm{coc}}}^{{n_{oc}}}\left( i \right) = \sum\limits_{k = 1}^N {E_{{\rm{ctsl}}}^k} \left( i \right) = \sum\limits_{k = 1}^N {\sum\limits_{m = 1}^L {E_{{\rm{rc}}}^{\left( {m,k} \right)}} } \left( i \right),$ (8)

Erc(m, k)(i)代表第k个时隙中第m个轮周期中, 单个节点i所消耗的能量。结合式(3)~(8), 可以得到Ecocnoc(i)的另一种形式如下

 $E_{{\rm{coc}}}^{{n_{oc}}}\left( i \right) = \sum\limits_{k = 1}^N {\sum\limits_{m = 1}^L {\left( {\sum\limits_{l = 1}^u {E_{{\rm{ch}}}^{\left( {l,m,k} \right)}} \left( i \right) + \sum\limits_{j = 1}^{q/p - u} {E_{{\rm{cm}}}^{\left( {j,m,k} \right)}} \left( i \right)} \right)} } ,$ (9)

 $E_{{\rm{copc}}}^{{n_{oc}}}\left( i \right) \ne E_{{\rm{copc}}}^{{n_{oc}}}\left( {i + 1} \right)\;\;\;\left( {i = 1,2,3, \cdots } \right),$ (10)
 $E_{{\rm{copc}}}^{{n_{oc}}}\left( i \right) \ne E_{{\rm{copc}}}^{{n_{oc}} + 1}\left( i \right)\;\;\;\left( {i = 1,2,3, \cdots } \right),$ (11)

 $E_{{\rm{coc}}}^{{n_{oc}}}\left( i \right) \le E_{{\rm{hoc}}}^{{n_{oc}}}\left( i \right),$ (12)

 图 3 能量收集与预算的过程 Fig. 3 Process of Energy Harvesting and Budgeting

 $E_{{\rm{coc}}}^{{n_{oc}}}\left( i \right) = E_{{\rm{bud}}}^{{n_{oc}}}\left( i \right) = E_{{\rm{hoc}}}^{{n_{oc}}}\left( i \right),$ (13)

 $E_{{\rm{avec}}}^{{n_{oc}}}\left( i \right) = \frac{{\left( {q/p} \right){T_r}E_{{\rm{coc}}}^{{n_{oc}}}\left( i \right)}}{{{\eta _{{n_{oc}}}}N{T_{{\rm{slt}}}}}},$ (14)

 $E_{{\rm{avec}}}^{{n_{oc}}} = \frac{1}{q}\sum\limits_{i = 1}^q {E_{{\rm{avec}}}^{{n_{oc}}}\left( i \right)} ,$ (15)

 ${\eta _{{n_{oc}} + 1}} = \min \left( {\max \left( {\frac{{\left( {q/p} \right){T_r}E_{{\rm{bud}}}^{{n_{oc}} + 1}}}{{{T_{oc}}E_{{\rm{avec}}}^{{n_{oc}}}}},{\eta _{\min }}} \right),1} \right),$ (16)

 $\left\{ \begin{array}{l} E_{{\rm{coc}}}^{{n_{oc}} + 1}\left( i \right) = \sum\limits_{k = 1}^N {\sum\limits_{m = 1}^{L_{{n_{oc}} + 1}} {\left( {\sum\limits_{l = 1}^u {E_{{\rm{ch}}}^{\left( {l,m,k} \right)}} \left( i \right) + \sum\limits_{j = 1}^{q/p - 1} {E_{{\rm{cm}}}^{\left( {j,m,k} \right)}} \left( i \right)} \right)} } ,\\ {L_{{n_{oc}} + 1}} = \left\{ \begin{array}{l} \left[ {\frac{{{\eta _{{n_{oc}} + 1}}{T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}}} \right]\;\;\;\;\;\;\;\left( {\frac{{{\eta _{{n_{oc}} + 1}}{T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}} - \left[ {\frac{{{\eta _{{n_{oc}} + 1}}{T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}}} \right] < 0.5} \right),\\ \left[ {\frac{{{\eta _{{n_{oc}} + 1}}{T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}}} \right] + 1\;\;\;\left( {\frac{{{\eta _{{n_{oc}} + 1}}{T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}} - \left[ {\frac{{{\eta _{{n_{oc}} + 1}}{T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}}} \right] \ge 0.5} \right), \end{array} \right.\\ {\eta _{{n_{oc}} + 1}} = \min \left( {\max \left( {\frac{{\left( {q/p} \right){T_r}E_{{\rm{bud}}}^{{n_{oc}} + 1}}}{{{T_{oc}}E_{{\rm{avec}}}^{{n_{oc}}}}},{\eta _{\min }}} \right),1} \right) \end{array} \right.$ (17)

 $E_{{\rm{coc}}}^{{n_{oc}} + 1}\left( i \right) = f\left( {E_{{\rm{coc}}}^{{n_{oc}}}\left( i \right)} \right),$ (18)

 ${f_\Delta }\left( {{\eta _{{n_{oc}}}}} \right) = E_{{\rm{coc}}}^{{n_{oc}}}\left( i \right) - E_{{\rm{bud}}}^{{n_{oc}}}\left( i \right),$ (19)

 ${f_\Delta }\left( {{\eta _{{n_{oc}}}}} \right) = \left\{ \begin{array}{l} > 0\;\;\;\left( {{\eta _{{n_{oc}}}} > \eta _{{n_{oc}}}^ * } \right),\\ = 0\;\;\;\left( {{\eta _{{n_{oc}}}} = \eta _{{n_{oc}}}^ * } \right),\\ < 0\;\;\;\;\left( {{\eta _{{n_{oc}}}} < \eta _{{n_{oc}}}^ * } \right), \end{array} \right.$ (20)

 $\left( {E_{{\rm{rc}}}^{\left( {m,k} \right)}\left( i \right) - E_{{\rm{avec}}}^{{n_{oc}}}\left( i \right)} \right) \sim N\left( {0,{\sigma ^2}} \right),$ (21)

 图 4 电池能量水平分段模型 Fig. 4 The Model of Battery Energy Level Segmentations

 ${B_{{\rm{thd}}}} = {B_{{\rm{orl}}}} - \frac{1}{q}\sum\limits_{i = 1}^q {E_{{\rm{coc}}}^1\left( i \right)} ,$ (22)

 $\left\{ \begin{array}{l} E_{{\rm{bud}}}^{{n_{oc}}}\left( i \right) = B_{{\rm{ava}}}^{{n_{oc}}}\left( i \right) - {B_{{\rm{thd}}}},\\ B_{{\rm{ava}}}^{{n_{oc}}}\left( i \right) = E_h^{{n_{oc}} - 1}\left( i \right) + B_{{\rm{res}}}^{{n_{oc}} - 1}\left( i \right), \end{array} \right.$ (23)

 $E_{{\rm{bud}}}^{{n_{oc}}} = \frac{1}{q}\sum\limits_{i = 1}^q {B_{{\rm{ava}}}^{{n_{oc}}}\left( i \right)} - {B_{{\rm{thd}}}},$ (24)

 $\begin{array}{l} E_{r - {\rm{coc}}}^{{n_{oc}}}\left( i \right) = E_{{\rm{coc}}}^{{n_{oc}}}\left( i \right) + {f_\Delta }\left( {{\eta _{{n_{oc}}}}} \right) = \\ \;\;\;\;\;\;\;\;\;\;\;\;2E_{{\rm{coc}}}^{{n_{oc}}}\left( i \right) - E_{{\rm{bud}}}^{{n_{oc}}}\left( i \right), \end{array}$ (25)

 $E_{r - {\rm{coc}}}^{{n_{oc}}}\left( i \right) = 2E_{{\rm{coc}}}^{{n_{oc}}}\left( i \right) - B_{{\rm{ava}}}^{{n_{oc}}}\left( i \right) + {B_{{\rm{thd}}}},$ (26)

 ${\eta _{{n_{oc}} + 1}} = \min \left( {\max \left( {\frac{{{\eta _{{n_{oc}}}}\sum\limits_{i = 1}^q {\left( {B_{{\rm{ava}}}^{{n_{ov}} + 1}\left( i \right) - {B_{{\rm{thd}}}}} \right)} }}{{\sum\limits_{i = 1}^q {\left( {2E_{{\rm{coc}}}^{{n_{oc}}}\left( i \right) - B_{{\rm{ava}}}^{{n_{oc}}}\left( i \right) + {B_{{\rm{thd}}}}} \right)} }},{\eta _{\min }}} \right),1} \right),$ (27)

 $\left\{ {{L_{{n_{oc}} + 1}} = \left\{ \begin{array}{l} \left[ {\frac{{{\eta _{{n_{oc}} + 1}}{T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}}} \right]\left( {\frac{{{\eta _{{n_{oc}} + 1}}{T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}} - \left[ {\frac{{{\eta _{{n_{oc}} + 1}}{T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}}} \right] < 0.5} \right),\\ \left[ {\frac{{{\eta _{{n_{oc}} + 1}}{T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}}} \right] + 1\;\;\;\;\left( {\frac{{{\eta _{{n_{oc}} + 1}}{T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}} - \left[ {\frac{{{\eta _{{n_{oc}} + 1}}{T_{{\rm{slt}}}}}}{{{T_{{\rm{rc}}}}}}} \right] \ge 0.5} \right), \end{array} \right.} \right.$ (28)
 $\left\{ \begin{array}{l} {\eta _{{n_{oc}} + 1}} = \min \left( {\max \left( {\frac{{{\eta _{{n_{oc}}}}\sum\limits_{i = 1}^q {\left( {B_{{\rm{ava}}}^{{n_{oc}} + 1}\left( i \right) - {B_{{\rm{thd}}}}} \right)} }}{{\sum\limits_{i = 1}^q {\left( {2E_{{\rm{coc}}}^{{n_{oc}}}\left( i \right) - B_{{\rm{ava}}}^{{n_{oc}}}\left( i \right) + {B_{{\rm{thd}}}}} \right)} }},{\eta _{\min }}} \right),1} \right),\\ \left( {{\eta _1} = 1} \right), \end{array} \right.$ (29)

3 仿真分析

 图 5 ENMM-HHE与P-FREE能量分配误差对比 Fig. 5 Comparison of energy assigning deviation between ENMM-HHE and P-FREE

4 实验测试与分析

 图 6 水质检测试验 Fig. 6 Water quality testing test

5 结语

 [1] Xu G B, Shen W M, Wang X B. Applications of wireless sensor networks in marine environment monitoring: a survey[J]. Sensors, 2014, 14(9): 16932-16954. [2] 刘鸣. 无线传感器网络技术发展分析[J]. 信息通信, 2016, 29(6): 286-287. LIU Ming. Analysis of the development of wireless sensor network technology[J]. Information & Communications, 2016, 29(6): 286-287. (in Chinese) [3] Atzori L, Iera A, Morabito G. The internet of things: a survey[J]. Computer Networks, 2010, 54(15): 2787-2805. [4] 吕雪. 无线传感器网络技术发展现状[J]. 信息通信, 2015(10): 169-170. LV Xue. Development status of wireless sensor network technology[J]. Information & Communications, 2015(10): 169-170. (in Chinese) [5] Raghavendra C S, Sivalingam K M, Znati T. Wireless sensor networks[M/OL]. Boston, MA: Springer US, 2004[2018-09-25]. https: //doi.org/10.1007/b117506. [6] 徐伟强, 吴铁军, 汪亚明, 等. 用于Ad Hoc网络的自适应多速率多播拥塞控制策略[J]. 软件学报, 2008(3): 769-778. XU Weiqiang, WU Tiejun, WANG Yaming, et al. Adaptive congestion control strategy for multirate multicast sessions in ad hoc networks[J]. Journal of Software, 2008(3): 769-778. (in Chinese) [7] Miorandi D, Sicari S, de Pellegrini F, et al. Internet of things: vision, applications and research challenges[J]. Ad Hoc Networks, 2012, 10(7): 1497-1516. [8] Xu G B, Shen W M, Wang X B. Applications of wireless sensor networks in marine environment monitoring: a survey[J]. Sensors, 2014, 14(9): 16932-16954. [9] 王伟.无线传感器网络若干关键技术研究[D].武汉: 华中科技大学, 2011. WANG Wei. Research on several key technologies of wireless sensor networks[D]. Wuhan: Huazhong University of Science and Technology, 2011. (in Chinese) [10] Mainetti L, Patrono L, Vilei A. Evolution of wireless sensor networks towards the internet of things: A survey[C/OL]. SoftCOM 2011, 19th International Conference on Software, Telecommunications and Computer Networks.New York, USA: IEEE, 2011: (2011-11-01)[2018-09-25].https://ieeexplore.ieee.org/document/6064380?arnumber=6064380&tag=1. [11] 何聪, 郭松涛. 可充电无线传感器网络的有向充电优化算法[J]. 重庆大学学报, 2019, 42(1): 88-97. HE Cong, GUO Songtao. Directed charging optimization algorithm in rechargeable wireless sensor networks[J]. Journal of Chongqing University, 2019, 42(1): 88-97. (in Chinese) [12] 芦浩. 太阳能光伏发电技术应用研究与普及[J]. 中国新技术新产品, 2016(16): 28-29. LU Hao. Application research and popularization of solar photovoltaic power generation technology[J]. New Technology & New Products of China, 2016(16): 28-29. (in Chinese) [13] Kosunalp S, Cihan A. Harvesting solar energy for limited-energy problem in wireless sensor networks[C/OL]. 2017 25th Signal Processing and Communications Applications Conference (SIU). New York, USA: IEEE, 2017: (2017-06-29)[2018-09-28]https: //ieeexplore.ieee.org/document/7960535. [14] Ramya R, Saravanakumar G, Ravi S. Energy harvesting in wireless sensor networks[M]. India: Springer India, 2016: 841-843. [15] Zhang X X, Fan R, Yang X C, et al. Two tracking control method to improve solar cell photoelectric efficiency[C/OL]. 2016 Chinese Control and Decision Conference (CCDC), Northeastern University, IEEE Singapore Industrial Electronics Session: Editorial Department of Control and Decision Making, 2016[2018-11-25]. https://ieeexplore.ieee.org/abstract/document/7531396. [16] Yang L, Lu Y Z, Zhong Y C, et al. A hybrid, game theory based, and distributed clustering protocol for wireless sensor networks[J]. Wireless Networks, 2016, 22(3): 1007-1021. [17] Basagni S, Naderi M Y, Petrioli C, et al. Wireless sensor networks with energy harvesting[M/OL]Mobile Ad Hoc Networking: Cutting Edge Directions, Second Edition. 2013-02-22.https://ieeexplore.ieee.org/document/6482731?denied. [18] 潘泽中.能量采集无线传感器网络的能量预测及分簇算法[D].南昌: 华东交通大学, 2016. PAN Zezhong. Energy prediction and clustering algorithm in energy harvesting wireless sensor network[D]. Nanchang: East China Jiaotong University, 2016. (in Chinese) http://cdmd.cnki.com.cn/Article/CDMD-10404-1016900404.htm [19] Peng S, Low C P. Throughput optimal energy neutral management for energy harvesting wireless sensor networks[C/OL]. 2012 IEEE Wireless Communications and Networking Conference (WCNC). New York, USA: IEEE, 2012: (2012-06-11)[2018-09-25].https://ieeexplore.ieee.org/document/6214186. [20] Babayo A A, Anisi M H, Ali I. A review on energy management schemes in energy harvesting wireless sensor networks[J]. Renewable and Sustainable Energy Reviews, 2017, 76: 1176-1184. [21] 杨柳.基于分簇结构的无线传感器网络节能路由协议研究[D].重庆: 重庆大学, 2016. YANG Liu. Study on cluster-based energy saving routing protocols for wireless sensor networks[D].Chongqing: Chongqing University, 2016. (in Chinese) http://cdmd.cnki.com.cn/Article/CDMD-10611-1016765753.htm