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首页> 外文期刊>IEEE transactions on industrial informatics >SynergyChain: Blockchain-Assisted Adaptive Cyber-Physical P2P Energy Trading
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SynergyChain: Blockchain-Assisted Adaptive Cyber-Physical P2P Energy Trading

机译：Synergychain：区块链辅助自适应网络 - 物理P2P能源交易

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摘要

Industrial investments into distributed energy resource technologies are increasing and playing a pivotal role in the global transactive energy, as part of a wider drive to provide a clean and stable source of energy. The management of prosumers, which consume and as well as generate energy, with heterogeneous energy sources is critical for sustainable and efficient energy trading procedures. This article proposes a blockchain-assisted adaptive model, namely SynergyChain, for improving the scalability and decentralization of the prosumer grouping mechanism in the context of peer-to-peer energy trading. Smart contracts are used for storing the transaction information and for the creation of the prosumer groups. SynergyChain integrates a reinforcement learning module to further improve the overall system performance and profitability by creating a self-adaptive grouping technique. The proposed SynergyChain is developed using Python and Solidity and has been tested using Ethereum test nets. The comprehensive analysis using the hourly energy consumption dataset shows a 39.7% improvement in the performance and scalability of the system as compared to the centralized systems. The evaluation results confirm that SynergyChain can reduce the request completion time along with an 18.3% improvement in the overall profitability of the system as compared to its counterparts.
机译：工业投资进入分布式能源资源技术正在增加并在全球变形能量中发挥关键作用，作为更广泛的驱动器的一部分，提供了一种干净稳定的能量来源。制度的管理，消费和生成能量，具有异质能源对于可持续和有效的能源交易程序至关重要。本文提出了一块区块链辅助自适应模型，即Synergychain，用于提高对等能源交易的背景下的检测机制的可扩展性和分散性。智能合同用于存储交易信息和创建法制群体。 SynergyChain通过创建自适应分组技术集成了加强学习模块，以进一步提高整体系统性能和盈利能力。建议的SynergyChain是使用Python和稳定性开发的，并使用Etereum试验网进行了测试。与集中系统相比，使用每小时能耗数据集的综合分析显示系统的性能和可扩展性的提高39.7％。评估结果证实，与同行相比，Synergychain可以减少请求完成时间，并在系统的整体盈利能力提高18.3％。

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