高压输电线路自动运维风险评估方法研究
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摘要
通过对高压输电线路自动运维风险评估,提高高压输电的安全性和稳定性,提出一种基于分段预白化模糊预测的高压输电线路自动运维风险评估方法。构建高压输电线路自动运维风险指数大数据模型,采用大数据属性特征分类方法进行运维风险决策,构建模糊决策函数,结合输电线路的自动运维风险评估数据的规则进行分段预白化匹配检测,对检测的运维风险评估数据进行模糊聚类处理,实现对运维风险评估数据的特征提取,根据特征提取结果进行最大熵分析,实现运维风险评估优化。仿真结果表明,采用该方法进行高压输电线路自动运维风险评估的决策准确性较好,风险评估的可靠性较强,置信度较高。
Through the risk assessment of automatic operation and maintenance of HV transmission lines,to improve the safety and stability of HV transmission lines,a risk assessment method for automatic operation and maintenance of high voltage transmission lines based on segmented prewhitening fuzzy prediction is proposed. Big data model of automatic operation and maintenance risk index of high voltage transmission lines is constructed. The fuzzy decision function is constructed,and combined with the rules of automatic operation and maintenance risk assessment data of transmission lines,the prewhitening matching detection is carried out,and the detected operation and maintenance risk assessment data are processed by fuzzy clustering. The feature extraction of operational and maintenance risk assessment data is realized,the maximum entropy analysis is carried out according to the feature extraction results,and the optimization of operational and maintenance risk assessment is realized. The simulation results show that,using this method,the decision-making accuracy,reliability and confidence of automatic operation and maintenance risk assessment for HV transmission lines are better.
Through the risk assessment of automatic operation and maintenance of HV transmission lines,to improve the safety and stability of HV transmission lines,a risk assessment method for automatic operation and maintenance of high voltage transmission lines based on segmented prewhitening fuzzy prediction is proposed. Big data model of automatic operation and maintenance risk index of high voltage transmission lines is constructed. The fuzzy decision function is constructed,and combined with the rules of automatic operation and maintenance risk assessment data of transmission lines,the prewhitening matching detection is carried out,and the detected operation and maintenance risk assessment data are processed by fuzzy clustering. The feature extraction of operational and maintenance risk assessment data is realized,the maximum entropy analysis is carried out according to the feature extraction results,and the optimization of operational and maintenance risk assessment is realized. The simulation results show that,using this method,the decision-making accuracy,reliability and confidence of automatic operation and maintenance risk assessment for HV transmission lines are better.
引文
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[2] Jing Q b,Hao F,Wang Q. A multivariable IMC-PID method for non-square large time delay systems using NPSO algorithm[J]. J of Process Control,2014,23(5):649-663.
[3]黄伟,庞琳,曹彬,等.基于分区解耦的配电网状态估计的分布式并行计算[J].电力系统保护与控制,2014,42(15):45-51.
[4]张建华,曾博,张玉莹,等.主动配电网规划关键问题与研究展望[J].电工技术学报,2014,29(2):13-23.
[5] LIN T y,SANTOSO H A,and WU K R. Global sensor deployment and local coverage-aware recovery schemes for smart environments[J]. IEEE Transactions on Mobile Computing,2015,14(7):1382-1396.
[6]陈盛,吕敏.电力用户高压输电线路运维风险评估数据采集系统及其应用[J].供用电,2011,28(4):45-49.
[7]张巍,阎立.下一代互联网在智能电网中的应用[J].电力系统通信,2012,33(242):95-100.
[8]陈雯雯,王亚林,周杰.三维统计信道中的多普勒效应及其信号分析[J].计算机科学,2017,44(3):84-88,131.
[9]刘备,谭新明,曹文彬. Spark Streaming动态资源分配策略[J].计算机应用,2017,37(6):1574-1579.
[10]翟雁,郭阳宽,祝连庆,等.步进电机模糊PID闭环控制系统仿真研究[J].现代电子技术,2015,38(11):146-149.
[11]丁青青,鲁伟,徐长波,等.三相并联混合有源电力滤波器的无源控制策略[J].电机与控制学报,2014,18(05):1-6.
[12] Chiranjeeevi T,Vijetha I V V,Chakravarthi B,et al. Tuning and control of multi-variable systems[J]. Int J of Electronics and Electrical Engineering,2014,2(4):309-320.
[13]刘倩,谭文,李东海.一种多变量自抗扰控制结构的设计研究[J].华北电力大学学报,2014,41(6):97-103.
[14]毛长涛,肖宗水.智能用电大规模电能信息采集运维管理技术研究[D].济南:山东大学,2013.
[15] DONG G L,RYU K S,BASHIR M,et al. Discovering medical knowledge using association rule mining in young adults with acute myocardial infarction[J]. Journal of Medical Systems,2013,37(2):1-10.
[16] KHALILI A,SAMI A. Sys Detect:a systematic approach to critical state determination for industrial intrusion detection systems using Apriori algorithm[J]. Journal of Process Control,2015,2776:154-160.