Research on Energy Trading Mechanism of New Energy Vehicles Based on Cobweb Model under Blockchain
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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。Abstract: Considering how to solve the problem of insufficient driving timeliness under the constraint of limited on-board energy resources of new energy vehicles, a distributed energy trading mechanism under the blockchain is proposed. Firstly, a new energy vehicle energy trading network based on the blockchain is built, and the privacy of energy trading through the Proof of Reputation (PoR) consensus mechanism is ensured. Then, based on the convergent spider web, a nonlinear pricing negotiation algorithm is designed, which combines with the blockchain technology to store the vehicle reputation database in a distributed way, to ensure that both energy trading parties can at least obtain the optimal pricing under the condition of meeting the weak Pareto effect. Finally, through simulation, the effectiveness and convergence of the proposed algorithm under the blockchain are verified, and the optimal step size and its coefficients of the algorithm are obtained.
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Key words:
- Internet of vehicular /
- New energy vehicles /
- Energy trading /
- Blockchain /
- Convergent spider web
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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$ 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 $\left[10,30\right]次/10\;\mathrm{min}$ 表 2 调幅参数及其系数
$ \gamma $ 0.05 0.1 0.15 ··· 0.95 $ \delta _k^{}(i) $ 0.1 0.2 0.3 ··· 2 -
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