{"title":"Accurate time synchronization of power reference station based on BD3 system","authors":"Ting Zou, Yuchen Huang, Zhanqiang Cheng, Jinshen Liu, Hongwei Guo","doi":"10.1016/j.gloei.2023.06.007","DOIUrl":null,"url":null,"abstract":"<div><p>A Beidou 3 (BD3) system-based power reference station can provide high-precision time synchronization for power distribution systems by sending synchronization data packets to devices in a multi-hop routing fashion. However, optimizing route selection to reduce both time synchronization error and delay is a challenging problem. In this paper, we establish a software-defined network-enabled power reference station time synchronization framework based on BD3. Then, we formulate the joint problem to minimize cumulative synchronization error and delay through multi-hop route selection optimization. A back propagation (BP) neural network-improved intelligent time synchronization route selection algorithm named BP-RS is proposed to learn the optimal route selection, which uses a BP neural network to dynamically adjust the exploration factor to achieve rapid convergence. Simulation results show the superior performance of BP-RS in synchronization delay, synchronization error, and adaptability with changing routing topologies.</p></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"6 3","pages":"Pages 334-342"},"PeriodicalIF":1.9000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Energy Interconnection","FirstCategoryId":"1087","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2096511723000506","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
A Beidou 3 (BD3) system-based power reference station can provide high-precision time synchronization for power distribution systems by sending synchronization data packets to devices in a multi-hop routing fashion. However, optimizing route selection to reduce both time synchronization error and delay is a challenging problem. In this paper, we establish a software-defined network-enabled power reference station time synchronization framework based on BD3. Then, we formulate the joint problem to minimize cumulative synchronization error and delay through multi-hop route selection optimization. A back propagation (BP) neural network-improved intelligent time synchronization route selection algorithm named BP-RS is proposed to learn the optimal route selection, which uses a BP neural network to dynamically adjust the exploration factor to achieve rapid convergence. Simulation results show the superior performance of BP-RS in synchronization delay, synchronization error, and adaptability with changing routing topologies.