高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

区块链下基于蛛网模型的新能源汽车能源交易机制研究

张海波 徐蓬勃 王汝言 贺晓帆 刘富

张海波, 徐蓬勃, 王汝言, 贺晓帆, 刘富. 区块链下基于蛛网模型的新能源汽车能源交易机制研究[J]. 电子与信息学报, 2023, 45(12): 4245-4253. doi: 10.11999/JEIT221386
引用本文: 张海波, 徐蓬勃, 王汝言, 贺晓帆, 刘富. 区块链下基于蛛网模型的新能源汽车能源交易机制研究[J]. 电子与信息学报, 2023, 45(12): 4245-4253. doi: 10.11999/JEIT221386
ZHANG Haibo, XU Pengbo, WANG Ruyan, HE Xiaofan, LIU Fu. Research on Energy Trading Mechanism of New Energy Vehicles Based on Cobweb Model under Blockchain[J]. Journal of Electronics & Information Technology, 2023, 45(12): 4245-4253. doi: 10.11999/JEIT221386
Citation: ZHANG Haibo, XU Pengbo, WANG Ruyan, HE Xiaofan, LIU Fu. Research on Energy Trading Mechanism of New Energy Vehicles Based on Cobweb Model under Blockchain[J]. Journal of Electronics & Information Technology, 2023, 45(12): 4245-4253. doi: 10.11999/JEIT221386

区块链下基于蛛网模型的新能源汽车能源交易机制研究

doi: 10.11999/JEIT221386
基金项目: 国家自然科学基金(62271094),长江学者和创新团队发展计划基金(IRT16R72),重庆市留创计划创新类资助项目(cx2020059)
详细信息
    作者简介:

    张海波:男,博士,副教授,研究方向为车联网、区块链以及能源交易等

    徐蓬勃:男,硕士生,研究方向为车联网、区块链以及能源交易等

    王汝言:男,博士,教授,研究方向为泛在网络、多媒体信息处理等

    贺晓帆:男,博士,教授,研究方向为车联网资源优化等

    刘富:男, 助理工程师,研究方向为智慧照明等

    通讯作者:

    徐蓬勃 1209094830@qq.com

  • 中图分类号: TN915

Research on Energy Trading Mechanism of New Energy Vehicles Based on Cobweb Model under Blockchain

Funds: The National Natural Science Foundation of China (62271094), The Program for Changjiang Scholars and Innovative Research Team in University (IRT16R72), The Innovation Funded Projects of Chongqing Overseas Students’ Innovation Program (cx2020059)
  • 摘要: 针对在新能源汽车有限的车载能源资源约束条件下,如何解决行驶时效性不足的问题,该文提出一种区块链下的分布式能源交易机制。首先基于区块链构建新能源汽车能源交易网络,并通过信誉值共识(PoR)机制确保能源交易的隐私性。然后,基于收敛型蛛网设计了非线性定价协商算法,联合区块链技术分布式存储车辆信誉值数据库,确保能源交易双方至少能在满足弱帕累托效应的情况下获得最优定价。最后通过仿真,验证了所提算法在区块链下的有效性和收敛性,并求出该算法的最优步长及其系数。
  • 图  1  车联网中能源交易系统模型图

    图  2  区块链下V2V能源交易模型图

    图  3  标准收敛型蛛网

    图  4  改良后收敛型蛛网

    图  5  迭代次数散点图

    图  6  迭代次数曲面图

    图  7  γ和δ对收敛次数的影响

    图  8  不同方法下的迭代次数对比图

    算法1 基于蛛网模型的迭代自适应定价协商算法
     输入:${p_j},o_k^{}(i),\delta _k^{}(i),d_i^B,d_i^{\exp },U'_B,U'_S$
     输出:$ p*,d* $;
     (1) 初始化:最大迭代次数$ M $,$ \varepsilon > 0 $,参数$ \gamma \in (0,1) $,初始步长 $ \delta (0) > \gamma \varepsilon $
     (2)  while $ \varepsilon > {10^{ - 3}} $ and $i \le M$ do
     (3)  $ {o_k}(i) = \neg (p(i + 1) > p(i) > p(i - 1) \vee p(i + 1) < p(i) < p(i - 1)) $
     (4)  if $ {o_k}(i) = 0 $
     (5)  then $ {\delta _k}(i + 1) = \left[ {1 - {o_k}(i)} \right]{\delta _k}(i) + {o_k}(i)\gamma {\delta _k}(i) $, $U'_B = U'_B \cdot \delta (i + 1)$, $U'_S = U'_S \cdot \delta (i + 1)$
     (6)  if $U'_B > U'_S$
     (7)  then $ {o_k}(i) = 1 $
     (8)  if $ {o_k}(i) = 1 $
     (9)  then $ {\delta _k}(i + 1) = \left[ {1 - {o_k}(i)} \right]{\delta _k}(i) + {o_k}(i)\gamma {\delta _k}(i) $, $U'_B = {( - 1)^j}U'_B \cdot \delta (i + 1)$, $U'_S = {( - 1)^j}U'_S \cdot \delta (i + 1)$, $ j + + $
     (10) $ \varepsilon = {\delta _k}(i) - {\delta _k}(i - 1), $$ i + + $
     (11) end
     (12) 输出$ {p^*},{d^*} $,其中${p^*} = U'_B ,{d^*} = U'_B$
    下载: 导出CSV

    表  1  车联网网络节点性能参数表

    参数名称取值
    MAC协议802.11 p
    车辆数量500 辆
    稳定通信范围200~500 m
    最大车速60 km/h
    道路长度5 km
    车辆长度5 m
    道路范围$\left( {2000 \times 2700} \right)\;{{\rm{m}}^2}$
    RSU覆盖范围$\left[ {300,500} \right]\;{\rm{m}}$
    声誉阈值0.5
    消息频率$\left[10,30\right]次/10\;\mathrm{min}$
    下载: 导出CSV

    表  2  调幅参数及其系数

    $ \gamma $
    0.050.10.15···0.95
    $ \delta _k^{}(i) $0.10.20.3···2
    下载: 导出CSV
  • [1] CONNOR W D, WANG Yongqiang, MALIKOPOULOS A A, et al. Impact of connectivity on energy consumption and battery life for electric vehicles[J]. IEEE Transactions on Intelligent Vehicles, 2021, 6(1): 14–23. doi: 10.1109/TIV.2020.3032642
    [2] TIAN Daxin, ZHOU Jianshan, WANG Yunpeng, et al. Channel access optimization with adaptive congestion pricing for cognitive vehicular networks: An evolutionary game approach[J]. IEEE Transactions on Mobile Computing, 2020, 19(4): 803–820. doi: 10.1109/TMC.2019.2901471
    [3] HASSIJA V, CHAMOLA V, GARG S, et al. A blockchain-based framework for lightweight data sharing and energy trading in V2G network[J]. IEEE Transactions on Vehicular Technology, 2020, 69(6): 5799–5812. doi: 10.1109/TVT.2020.2967052
    [4] MACHURA P, DE SANTIS V, and LI Quan. Driving range of electric vehicles charged by wireless power transfer[J]. IEEE Transactions on Vehicular Technology, 2020, 69(6): 5968–5982. doi: 10.1109/TVT.2020.2984386
    [5] BULUT E, KISACIKOGLU M C, and AKKAYA K. Spatio-temporal non-intrusive direct V2V charge sharing coordination[J]. IEEE Transactions on Vehicular Technology, 2019, 68(10): 9385–9398. doi: 10.1109/TVT.2019.2931954
    [6] OCEANO A, RODELLA C, RIZZO R, et al. Grid balancing support through Electric Vehicles mobile storage[C]. 2020 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), Sorrento, Italy, 2020: 108–113.
    [7] PARK L, JEONG S, LAKEW D S, et al. New challenges of wireless power transfer and secured billing for internet of electric vehicles[J]. IEEE Communications Magazine, 2019, 57(3): 118–124. doi: 10.1109/MCOM.2018.1800291
    [8] UCER E, BUCKREUS R, KISACIKOGLU M C, et al. A flexible V2V charger as a new layer of vehicle-grid integration framework[C]. 2019 IEEE Transportation Electrification Conference and Expo (ITEC), Detroit, USA, 2019: 1–7.
    [9] WANG Jiashuo. Analyzing the application of blockchain and artificial intelligence in new energy vehicle transactions from a data security perspective[C]. 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI), Tirunelveli, India, 2022: 992–995.
    [10] OKWUIBE G C, LI Zeguang, BRENNER T, et al. A blockchain based electric vehicle smart charging system with flexibility[J]. IFAC-PapersOnLine, 2020, 53(2): 13557–13561. doi: 10.1016/j.ifacol.2020.12.800
    [11] ASHFAQ T, JAVAID N, JAVED M U, et al. Secure energy trading for electric vehicles using consortium blockchain and k-nearest neighbor[C]. 2020 International Wireless Communications and Mobile Computing (IWCMC), Limassol, Cyprus, 2020: 2235–2239.
    [12] SUN Gang, DAI Miao, ZHANG Feng, et al. Blockchain-enhanced high-confidence energy sharing in internet of electric vehicles[J]. IEEE Internet of Things Journal, 2020, 7(9): 7868–7882. doi: 10.1109/JIOT.2020.2992994
    [13] ALVARO R, GONZÁLEZ J, GAMALLO C, et al. Vehicle to vehicle energy exchange in smart grid applications[C]. 2014 International Conference on Connected Vehicles and Expo (ICCVE), Vienna, Austria, 2014: 178–184.
    [14] LÜTH A, ZEPTER J M, DEL GRANADO P C, et al. Local electricity market designs for peer-to-peer trading: The role of battery flexibility[J]. Applied Energy, 2018, 229: 1233–1243. doi: 10.1016/j.apenergy.2018.08.004
    [15] LEE J T, HENRIQUEZ-AUBA R, POOLLA B K, et al. Callaway. Pricing and energy trading in peer-to-peer zero marginal-cost microgrids[J]. IEEE Transactions on Smart Grid, 2022, 13(1): 702–714. doi: 10.1109/TSG.2021.3122879
    [16] PAUDEL A, CHAUDHARI K, LONG C, et al. Peer-to-peer energy trading in a prosumer-based community microgrid: A game-theoretic model[J]. IEEE Transactions on Industrial Electronics, 2019, 66(8): 6087–6097. doi: 10.1109/TIE.2018.2874578
    [17] WANG Yuntao, SU Zhou, XU Qichao, et al. A novel charging scheme for electric vehicles with smart communities in vehicular networks[J]. IEEE Transactions on Vehicular Technology, 2019, 68(9): 8487–8501. doi: 10.1109/TVT.2019.2923851
    [18] XIA Shengnan, LIN Feilong, CHEN Zhongyu, et al. A Bayesian game based vehicle-to-vehicle electricity trading scheme for blockchain-enabled internet of vehicles[J]. IEEE Transactions on Vehicular Technology, 2020, 69(7): 6856–6868. doi: 10.1109/TVT.2020.2990443
    [19] ABISHU H N, SEID A M, YACOB Y H, et al. Consensus mechanism for blockchain-enabled vehicle-to-vehicle energy trading in the internet of electric vehicles[J]. IEEE Transactions on Vehicular Technology, 2022, 71(1): 946–960. doi: 10.1109/TVT.2021.3129828
    [20] AITZHAN N Z and SVETINOVIC D. Security and privacy in decentralized energy trading through multi-signatures, blockchain and anonymous messaging streams[J]. IEEE Transactions on Dependable and Secure Computing, 2018, 15(5): 840–852. doi: 10.1109/TDSC.2016.2616861
    [21] ARAVINDHAN K and DHAS C S G. Destination-aware context-based routing protocol with hybrid soft computing cluster algorithm for VANET[J]. Soft Computing, 2019, 23(8): 2499–2507. doi: 10.1007/s00500-018-03685-7
    [22] LI Jueyou, LI Chaojie, XU Yan, et al. Noncooperative game-based distributed charging control for plug-in electric vehicles in distribution networks[J]. IEEE Transactions on Industrial Informatics, 2018, 14(1): 301–310. doi: 10.1109/TII.2016.2632761
  • 加载中
图(8) / 表(3)
计量
  • 文章访问数:  323
  • HTML全文浏览量:  135
  • PDF下载量:  107
  • 被引次数: 0
出版历程
  • 收稿日期:  2022-11-04
  • 修回日期:  2023-05-10
  • 网络出版日期:  2023-05-16
  • 刊出日期:  2023-12-26

目录

    /

    返回文章
    返回