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面向电网调控任务的实时数据分布式计算技术综述
作者:
作者单位:

1.南瑞集团有限公司（国网电力科学研究院）;2.国网江苏省电力有限公司电力调度控制中心;3.南京信息工程大学

基金项目:

国电南瑞南京控制系统有限公司科技信息项目(No.2023h581)


Survey of distributed computing technology for real-time data in power grid control tasks
Author:
Affiliation:

1.NARI Limited Liability Company of State Grid Electric Power Research Institute;2.State Grid Jiangsu Electric Power Co., Ltd. Power Dispatch and Control Center;3.Nanjing University of Information Science &4.amp;5.Technology

Fund Project:

State Grid Nanree Nanjing Control System Co., Ltd. Science and Technology Information Project(No.2023h581)

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    摘要:

    网调控实时数据分布式计算技术是一种通过将计算任务分布到多个计算节点并行执行的技术，用于处理电网调控中的大规模实时数据，是近年来电力行业发展的重要方向之一。本文综合分析了分布式计算技术在电网调控实时数据中的应用现状，并探讨了其未来的发展趋势。首先，本文阐述了电网实时数据的特征及处理方式；接着，讨论了分布式计算技术的研究现状，以及其在电网实时数据中的应用，并扩展到新兴分布式计算技术的发展及其在电网中的应用；最后，基于当前的研究现状和发展趋势，对电网调控实时数据的分布式计算技术进行开放性讨论和展望。

    Abstract:

    Distributed computing technology for real-time data in power grid regulation is considered to be one of the important directions in the recent development of the power industry. It involves the distribution of computing tasks to multiple computing nodes for parallel execution, aiming to handle large-scale real-time data in power grid regulation. The current application status of distributed computing technology in real-time data for power grid regulation was comprehensively analyzed in this article, and its future development trends are explored. Firstly, the characteristics and processing methods of real-time data in power grids are discussed ; then, the current state of research on distributed computing technology is examined, along with its application in the context of real-time data in power grids, and an exploration of the development of emerging distributed computing technologies and their integration into power grid applications is presented; finally, an open discussion and future outlook for the distributed computing technology of real-time data in power grid regulation are provided, based on the current research status and trends.

    参考文献
    [1] YEHUDA A, GAL G, Boaz S P. Distributed computing with the cloud [J]. Distributed Computing, 2024, 37(1): 1-18.
    [2] 王瀚橙,戴海鹏,陈志鹏,等.基于MapReduce的大规模网络社区发现算法[J/OL].计算机科学,1-11[2024-03-12].http://kns.cnki.net/kcms/ detail/50.1075.TP.20240221.1934.026.html.
    [3] 李波,赵瑞锋,卢建刚,等.基于聚类算法的电力大数据信息分析系统研究[J].自动化仪表,2023,44(08):84-90.
    [4] 黄新宇,高嵩,邱刚,等.基于MapReduce的并行化电网运行数据处理方法研究[J].电子设计工程,2024,32(04):98-102.
    [5] 毛先胤,文屹,马晓红,等.基于电力大数据的多源异构数据融合技术研究与应用[J].电力大数据,2020,23(08):33-39.
    [6] 厍向阳,张玲.基于Hadoop的FP-Growth关联规则并行改进算法[J].计算机应用研究,2018,35(1):1-6.
    [7] 刘南艳,贺敏,赵建文.基于大数据平台的电力负荷预测[J].现代电子技术,2018,41(20):153-156.
    [8] 刘琪琛,雷景生,郝珈玮,等.基于Spark平台和并行随机森林回归算法的短期电力负荷预测[J].电力建设,2017,38(10):84-92.
    [9] 梁海东,赵晓燕.基于数据挖掘的电能计量设备异常并行诊断研究[J].自动化与仪器仪表,2021(02):231-234.
    [10] CAIYAN P, SHUAI Z, XIAONING Z. Research on anomaly detection of wireless data acquisition in power system based on spark[J]. Energy Reports, 2022, 8(S4): 1392-1404.
    [11] 张磊,刘辛彤,蔡硕,等.基于Storm架构的电力物联网流数据处理[J].电力系统保护与控制,2021,49(20):112-119.
    [12] 赵铭滕,朱永利.基于Storm的变压器PRPD参数提取与模式构造[J].计算机应用与软件,2022,39(02):44-48.
    [13] 黄荣辉,周伟,张顺斌,等.基于Storm计算的电力设备并行诊断模型构建及仿真[J].自动化与仪器仪表,2021,(01):81-84.
    [14] 赵鹏杰,吴俊勇,林凯骏,等.基于一致性算法的多微电网点对点分布式能量交易策略[J].电网技术,2023,47(01):205-218.
    [15] 巨云涛,李嘉伟,陈浩,等.基于局部几何参数化和JFNG算法的微电网群分布式连续潮流计算[J].电力自动化设备,2023,43(06):71-77+136.
    [16] 巨云涛,张紫枫,刘文武,等.考虑限幅约束的多区域互联电网全分布式潮流算法[J].电力系统保护与控制,2022,50(07):58-68.
    [17] 曾琮,黄强,陈德,等.基于改进纵横交叉算法的电网最优潮流计算[J].中国电力,2021,54(09):9-16.
    [18] 杨溢,郭志忠.含电磁环网的输配电网全局动态潮流主从分裂算法[J].电力系统自动化,2019,43(14):143-150.
    [19] WANG R ,SUN Q ,LIU X , et al. Power flow calculation basedon local controller impedance features for the AC microgrid? with distributed generations[J].IET Energy Systems Integration,2019,1(3):202-209.
    [20] WANG D ,ZHOU F ,LI J .Cloud-based parallel power flow??? calculation using resilient distributed datasets and directed acyclicgraph[J].Journal of Modern Power Systems and Clean Energy,2018,7(1):65-77.
    [21] MO Y, MURRAY R M .Privacy Preserving Average Consensus[J].IEEE Transactions on Automatic Control, 2017, 62(2):1-1
    [22] DUAN J , ZENG W , CHOW M Y .Resilient Distributed DC Optimal Power Flow Against Data Integrity Attack[J].IEEE Transactions on Smart Grid, 2016:1-1
    [23] 应杰耀.基于物联网技术的智能电网数据安全问题研究进展[J].电子科技,2023,36(03):76-80.
    [24] ZHANG G , ZHANG F , MENG K ,et al. A distributed calculation method for robust day-ahead scheduling of integrated electricity-gas systems[J].International journal of electrical power and energy systems, 2022(3):136.
    [25] 林舜江,唐智强,谢煜铨,等.电-气混合系统安全约束最优能量流的分布式计算[J].华南理工大学学报(自然科学版),2020,48(07):36-46.
    [26] SONG L ,XIONG W , LONGSHOU H , et al. Blockchain-based decentralized federated learning method in edge computing environment[J].Applied Sciences,2023,13(3):1677-1677.
    [27] GUPTA, RUCHI, ALAM, et al. Survey on federated-learning approaches in distributed environment[J].Wireless Personal Communications,2022,125(2):1-22.
    [28] 谭军光,于全喜,孔海斌,等.城市电网调度控制云系统总体架构设计[J].自动化技术与应用,2019,38(05):67-69+86.
    [29] 贾金伟,吴旭鹏,李启本,等.基于并行计算的大数据挖掘在电网中的应用[J].电力与能源,2017,38(06):724-729.
    [30] ALORF A .edge-cloud computing for scheduling the energy consumption in smart grid[J].Computer Systems Science and Engineering,2023,46(1):273-286.
    [31] 黄冬梅,何立昂,孙锦中,等.基于边缘计算的电网假数据攻击分布式检测方法[J].电力系统保护与控制,2021,49(13):1-9.
    [32] LIHUA Z ,CHUNHUA L , BOPING L , et al. A secure storageand deletion verification scheme of microgrid data based on??? integrating blockchain into edge computing[J].Electronics,2022,11(23):4033-4033.
    [33] ZHANG X , HUANG C , GU D ,et al. Privacy-preserving statistical analysis over multi-dimensional aggregated data in edge??? computing-based smart grid systems[J].Journal of systems????? architecture, 2022(127-):127.
    [34] 陈嘉翊,孙晨雨,周欣桐,等.基于联邦学习和同态加密的电力数据预测模型本地保护[J].信息安全研究,2023,9(03):228-234.
    [35] 周毅斌,肖浩,裴玮,等.基于纵向联邦学习的微电网群协同优化运行与策略进化[J].电力系统自动化,2023,47(11):121-132.
    [36] 唐滢淇,董树锋,唐坤杰,等.基于输电网广播机制的改进输配互联电网异步状态估计方法[J].高电压技术,2021,47(07):2377-2386.
    [37] 方勇杰,王胜明,徐泰山,等.基于流程组态的电力系统安全稳定分析并发计算[J].电力系统保护与控制,2018,46(11):92-98.
    [38] 赵晋泉,张振伟,姚建国,等.基于广义主从分裂的输配电网一体化分布式无功优化方法[J].电力系统自动化,2019,43(03):108-115.
    [39] ARUL R ,DHIVYA S ,MEHSAL A , et al. Modernized?????? planning of smart grid based on distributed power generations? and energy storage systems using soft computing methods[J].?? Energies,2022,15(23):8889-8889.
    [40] MICHAEL K ,ALEXANDER M ,Philipp S , et al. Impact of grid partitioning algorithms on combined distributed AC optimal power flow and parallel dynamic power grid simulation[J].IET Generation, Transmission Distribution,2020,14(25):6133-6141.
    [41] 邵炜晖,许维胜,徐志宇,等.基于区块链的虚拟电厂模型研究[J].计算机科学,2018,45(02):25-31.
    [42] 李媛.面向智能电网监测的分布式数据流处理[J].电测与仪表,2023,60(08):121-124+163.
    [43] 李云波,张子立,张晋宾,等.基于区块链的分布式微电网交易与能源调度研究[J].华电技术,2020,42(08):24-31.
    [44] JACOBSON D ,DICKERMAN L .Distributed intelligence: A??? critical piece of the microgrid puzzle[J].The Electricity Journal,2019,32(5):10-13.
    [45] SAXENA K ,ABHYANKAR R A .Distributed architecture for self-organising smart distribution systems[J].IET Smart Grid,2018,1(4):113-122.
    [46] MIAO X ,YIMING F ,JIANXIONG L , et al. Finite time fully distributed consensus control for multi-agent system with input saturation and limited communication resources[J].International Journal of Control, Automation and Systems,2023,21(11):3659-3672.
    [47] DJEUNANG A R M ,ZINEB S ,DI M .optimization of distributed maintenance: design, scheduling and capacitated routing problem[J].IFAC PapersOnLine,2022,55(19):139-144.
    [48] 刘瑞奇,李博扬,高玉金,等.新型分布式计算系统中的异构任务调度框架[J].软件学报,2022,33(03):1005-1017.
    [49] 史佳雯,汪洋,张庚,等.面向电力通信网的分布式仿真系统[J].计算机工程与应用,2019,55(19):246-252.
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孙世明,唐元合,邰曈,魏学云,方巍.面向电网调控任务的实时数据分布式计算技术综述[J].南京信息工程大学学报,,():

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  • 收稿日期:2024-06-07
  • 最后修改日期:2024-07-12
  • 录用日期:2024-07-13

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