当前位置: X-MOL 学术IEEE Netw. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Blockchain and AI-Based Natural Gas Industrial IoT System: Architecture and Design Issues
IEEE NETWORK ( IF 9.3 ) Pub Date : 2020-09-18 , DOI: 10.1109/mnet.011.1900532
Yiming Miao , Ming Zhou , Ahmed Ghoneim

With the development of energy interconnection and increasing consumption of natural gas, the distributed energy supply and trusted-transaction- based natural gas Industrial Internet of Things (IIoT) has become one of the hottest research spots in the energy industry. This article puts forward natural gas IIoT architecture based on blockchain and AI, in order to address the defects of centralized energy supply architecture. The proposed architecture is introduced in detail from three aspects of infrastructure, side-chain of natural gas block based on data dimension, and backbone of natural gas block based on value dimension. Then the design issues on the integration existence of blockchain and AI in an actual natural gas IIoT scenario are discussed, including data association and interaction of blockchains, trusted identity authentication and management, energy source and virtual currency transformation, and so on. Next, an LSTM-based natural gas load prediction model is proposed by virtue of AI technology. The transaction model based on natural gas value and supply-demand relationship is also proposed by choosing the common natural gas application scenarios and taking advantage of blockchain technology. Experiments show that the proposed models can predict demand and output load of natural gas, while achieving the balance of interests of natural gas suppliers, users, and market in the transaction scenarios.

中文翻译:

区块链和基于AI的天然气工业物联网系统:架构和设计问题

随着能源互连的发展和天然气消耗的增加,基于分布式能源供应和基于信任交易的天然气工业物联网(IIoT)已成为能源行业最热门的研究热点之一。本文提出了一种基于区块链和AI的天然气IIoT架构,以解决集中式能源供应架构的缺陷。从基础设施,基于数据维度的天然气区块的侧链和基于价值维度的天然气区块的骨干这三个方面详细介绍了所提出的架构。然后讨论了在天然气IIoT实际场景中区块链与AI集成存在的设计问题,包括数据关联和区块链的交互,受信任的身份验证和管理,能源和虚拟货币转换等。接下来,借助AI技术提出了基于LSTM的天然气负荷预测模型。通过选择常见的天然气应用场景并利用区块链技术,提出了一种基于天然气价值与供求关系的交易模型。实验表明,所提出的模型可以预测天然气的需求和输出负荷,同时在交易场景中实现天然气供应商,用户和市场的利益平衡。通过选择常见的天然气应用场景并利用区块链技术,提出了一种基于天然气价值与供求关系的交易模型。实验表明,所提出的模型可以预测天然气的需求和输出负荷,同时在交易场景中实现天然气供应商,用户和市场的利益平衡。通过选择常见的天然气应用场景并利用区块链技术,提出了一种基于天然气价值与供求关系的交易模型。实验表明,所提出的模型可以预测天然气的需求和输出负荷,同时在交易场景中实现天然气供应商,用户和市场的利益平衡。
更新日期:2020-09-22
down
wechat
bug