高元海, 平健, 严正, 陈思捷, 沈翔宇. 能源区块链离散状态事件驱动仿真方法[J]. 中国电机工程学报, 2023, 43(18): 7115-7126. DOI: 10.13334/j.0258-8013.pcsee.221169
引用本文: 高元海, 平健, 严正, 陈思捷, 沈翔宇. 能源区块链离散状态事件驱动仿真方法[J]. 中国电机工程学报, 2023, 43(18): 7115-7126. DOI: 10.13334/j.0258-8013.pcsee.221169
GAO Yuanhai, PING Jian, YAN Zheng, CHEN Sijie, SHEN Xiangyu. Energy Blockchain Simulation Method Based on Discrete-state Event-driven Mechanism[J]. Proceedings of the CSEE, 2023, 43(18): 7115-7126. DOI: 10.13334/j.0258-8013.pcsee.221169
Citation: GAO Yuanhai, PING Jian, YAN Zheng, CHEN Sijie, SHEN Xiangyu. Energy Blockchain Simulation Method Based on Discrete-state Event-driven Mechanism[J]. Proceedings of the CSEE, 2023, 43(18): 7115-7126. DOI: 10.13334/j.0258-8013.pcsee.221169

能源区块链离散状态事件驱动仿真方法

Energy Blockchain Simulation Method Based on Discrete-state Event-driven Mechanism

  • 摘要: 区块链技术在能源领域具有广阔的应用前景,能源区块链的工程应用正逐步推进。现有能源区块链仿真方法仅能仿真小规模系统,且难以灵活测试能源区块链参数对运行效率的影响,无法分析含大规模节点的能源区块链性能。该文首次引入离散状态事件驱动仿真思想,提出灵活高效的大规模能源区块链仿真方法。首先,构建面向离散状态事件驱动的能源区块链仿真模型,仿真能源区块链节点和网络的核心功能。随后,设计了能源区块链的离散状态事件集和事件调度时序规则,驱动仿真模型动态运行。最后,开发了能源区块链仿真器,选取大规模分布式能源点对点交易场景验证了所提方法的有效性及仿真效率。结果表明,所提方法能够灵活高效地仿真大规模能源区块链,既可以验证智能合约的有效性,同时为能源区块链的参数配置提供仿真数据支撑。

     

    Abstract: Blockchain is a promising technology in the energy sector. Energy blockchain applications have been gradually developed. Existing energy blockchain simulation methods can only simulate small-scale systems, but cannot flexibly test the impact of energy blockchain parameters on operating efficiency, and cannot analyze the efficiency of large-scale energy blockchain applications. This paper introduces the concept of discrete-state event-driven simulation in energy blockchain simulation for the first time, and proposes a flexible and efficient simulation method for large-scale energy blockchains. First, to simulate the core functions of a node and communication network on blockchain, an energy blockchain simulation model is constructed for discrete-state event-driven simulation. Second, the discrete events and their scheduling rules are designed to drive the dynamic operation of the simulation model. Finally, an energy blockchain simulator is developed. The effectiveness and the efficiency of the proposed method are tested in a large-scale distributed energy resource peer-to-peer trading scenario. Simulation results show that the proposed method can flexibly and efficiently simulate a large-scale energy blockchain, verifying the correctness of smart contracts and providing simulation data for parameter configuration of energy blockchains.

     

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