基于轻量级模糊Petri网的两阶段共识赋能配电计量数据共享方法OA
A Two-stage Consensus-empowered Measurement Data Sharing Approach for Distribution Networks Based on Lightweight Fuzzy Petri Nets
随着配电网设备的广泛接入,计量数据呈指数级增长,海量配电计量数据的安全共享和交互溯源面临重要挑战.因此,提出一种基于轻量级模糊 Petri网(fuzzy Petri net,FPN)的两阶段共识赋能配电计量数据共享方法.首先,构建基于轻量级 FPN的两阶段共识赋能配电计量数据交互架构.然后,提出基于轻量级 FPN节点信任度评估的两阶段共识赋能配电计量数据共享方法,根据多维节点可信度指标选取簇头节点,完成自适应分簇,并生成对抗网络训练初始状态向量.随后,设置迭代次数阈值,减少轻量级FPN迭代次数,再采用 Top-J排序方法选取信任值较大的共识节点,完成簇内、簇间的两阶段共识.最后,通过仿真验证所提算法在节点信任度、共识时延、CPU占用率等方面的优越性,提高海量配电计量数据的安全共享和交互溯源能力.
With the widespread deployment of distribution network equipment,measurement data is growing exponentially.The secure sharing and interactive traceability of massive distribution measurement data present considerable challenges.Therefore,a two-stage consensus-empowered measurement data sharing approach for distribution networks is proposed based on lightweight fuzzy Petri nets(FPNs).First,a two-stage consensus-sharing architecture for distribution measurement data interaction is constructed based on lightweight FPN.Second,a two-stage consensus-empowerment measurement data approach for distribution networks is proposed based on lightweight FPN nodes credibility evaluation.Specifically,the cluster head nodes are selected for adaptive multi-dimensional node trust indicators.These multi-clustering based on dimensional node trust indicators are subsequently trained by a generative adversarial network(GAN)to generate the initial state vector,and an iteration threshold is set to reduce the number of lightweight FPN iterations.Third,the Top-J ranking method is utilized to select consensus nodes with higher trust values and to complete the two-stage consensus within and between clusters.Finally,the superiority of the proposed algorithm is validated through simulations in terms of nodes trustworthiness,consensus delay,and CPU occupancy.Moreover,the ability of secure sharing and interactive traceability of massive distribution measurement data is enhanced.
王珂;汤中卫;刘昊东;张孙烜;杨雨霏;周振宇
新能源电力系统国家重点实验室(华北电力大学),北京市 昌平区 102206新能源电力系统国家重点实验室(华北电力大学),北京市 昌平区 102206新能源电力系统国家重点实验室(华北电力大学),北京市 昌平区 102206新能源电力系统国家重点实验室(华北电力大学),北京市 昌平区 102206新能源电力系统国家重点实验室(华北电力大学),北京市 昌平区 102206新能源电力系统国家重点实验室(华北电力大学),北京市 昌平区 102206
信息技术与安全科学
自适应分簇轻量级模糊Petri网迭代次数阈值生成对抗网络Top-J排序方法簇内共识簇间共识
adaptive clusteringlightweight fuzzy Petri netiteration count thresholdgenerative adversarial networkTop-J sorting methodintra-cluster consensusinter-cluster consensus
《现代电力》 2026 (5)
833-841,9
国家电网有限公司科技项目(5700-202318300A-1-1-ZN). Science and Technology Project of State Grid Corporation(5700-202318300A-1-1-ZN).
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