基于数据融合的电力设备运维策略优化研究
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摘要
以实际案例分析为切入点,提出了基于数据融合的电力设备运维策略优化方法。首先在现有电力设备运维方式下对案例事故的处理方法及流程进行了剖析,指出了其所存在的局限性。然后,对现有电力数据对于运维的辅助信息进行充分挖掘,通过强化各系统间数据交互性,基于数据融合方法对案例所涉及的运维系统进行了优化和改造。最后展示了在新运维方式下,案例事故在处理方法、处理流程、及处理时间上所展现的优势,论证了本文所提出的电力设备运维策略优化方法的可行性。
This paper takes the actual case analysis as the starting point,it proposes a strategy optimization method for operation and maintenance of power equipment based on data fusion. At first, this paper analyzes the treatment method and process of the accident case under the existing operation and maintenance mode of power equipment,and points out its limitations. Then, the auxiliary information of operation and maintenance is fully mined for the existing power data, and the operation and maintenance system involved in the accident case is optimized and reformed by strengthening the data interactivity between different systems and based on data fusion method. Finally,it shows the advantages of accident case treatment in treatment method, treatment process and treatment time under the new mode of operation and maintenance.And it also demonstrates the correctness and feasibility of the strategy optimization method for operation and maintenance of power equipment proposed in this paper.
This paper takes the actual case analysis as the starting point,it proposes a strategy optimization method for operation and maintenance of power equipment based on data fusion. At first, this paper analyzes the treatment method and process of the accident case under the existing operation and maintenance mode of power equipment,and points out its limitations. Then, the auxiliary information of operation and maintenance is fully mined for the existing power data, and the operation and maintenance system involved in the accident case is optimized and reformed by strengthening the data interactivity between different systems and based on data fusion method. Finally,it shows the advantages of accident case treatment in treatment method, treatment process and treatment time under the new mode of operation and maintenance.And it also demonstrates the correctness and feasibility of the strategy optimization method for operation and maintenance of power equipment proposed in this paper.
引文
[1]潘可佳,王鑫,杨帆,母继元,杨懿.面向电力大数据的多源异构数据融合技术研究[J].机械与电子,2017,35(9):7-11.
[2]侯仁政,张岩,张小易,等.基于多源数据融合的电力系统故障诊断与评估平台开发[J].机电工程,2017,34(10):1173-1179.
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[5]刘同旭,谌业刚,宫玉洁.基于GIS平台的电力电缆实时在线监测系统研究[J].能源与环保,2017,39(7):77-82.
[6]于德明,陈方东,郭昕阳,赵雪松,张吉飞,王黎明.输电线路直升机激光扫描三维成像技术的应用[J].高电压技术,2011,37(3):711-717.
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[8]吴细珍.数据挖掘在电力企业中的应用[J].广东电力,2004,(1):40-43.
[9]李刚,刘燕,宋雨,尹军.基于信息融合的电力大数据可视化预处理方法[J].广东电力,2016,29(12):10-14.
[10]强东盛,高龙.大数据在电力调度中的应用[J].河北电力技术,2017,36(2):1-2,15.
[11]王守鹏,赵冬梅.电网故障诊断的研究综述与前景展望[J].电力系统自动化,2017,41(19):164-175.
[12]王飞,颜波,禹晋云.基于大数据的电力多维度分析系统设计与实现[J].电力信息与通信技术,2017,15(4):30-35.
[13]魏大千,王波,刘涤尘,陈得治,唐飞,郭珂.基于时序数据相关性挖掘的WAMS/SCADA数据融合方法[J].高电压技术,2017,15(4):30-35.
[14]秦圣辉,尤飞,王振华,张云.山火诱发500kV及以上输电线路跳闸事故分析[J].消防科学与技术,2017,36(5):712-716.
[15]宫宇,吕金壮.大数据挖掘分析在电力设备状态评估中的应用[J].南方电网技术,2014,8(6):74-77.
[2]侯仁政,张岩,张小易,等.基于多源数据融合的电力系统故障诊断与评估平台开发[J].机电工程,2017,34(10):1173-1179.
[3]蔡徽.广东电网电力大数据现状及主要发展思路[J].广东电力,2014,27(12):11-14.
[4]郇嘉嘉,王钢,李海锋,汪隆君,李平.电网停电综合管理与分析决策系统的研究与开发[J].电力系统保护与控制,2012,40(8):140-146,150.
[5]刘同旭,谌业刚,宫玉洁.基于GIS平台的电力电缆实时在线监测系统研究[J].能源与环保,2017,39(7):77-82.
[6]于德明,陈方东,郭昕阳,赵雪松,张吉飞,王黎明.输电线路直升机激光扫描三维成像技术的应用[J].高电压技术,2011,37(3):711-717.
[7]卢建昌,樊围国.大数据时代下数据挖掘技术在电力企业中的应用[J].广东电力,2014,27(9):88-94.
[8]吴细珍.数据挖掘在电力企业中的应用[J].广东电力,2004,(1):40-43.
[9]李刚,刘燕,宋雨,尹军.基于信息融合的电力大数据可视化预处理方法[J].广东电力,2016,29(12):10-14.
[10]强东盛,高龙.大数据在电力调度中的应用[J].河北电力技术,2017,36(2):1-2,15.
[11]王守鹏,赵冬梅.电网故障诊断的研究综述与前景展望[J].电力系统自动化,2017,41(19):164-175.
[12]王飞,颜波,禹晋云.基于大数据的电力多维度分析系统设计与实现[J].电力信息与通信技术,2017,15(4):30-35.
[13]魏大千,王波,刘涤尘,陈得治,唐飞,郭珂.基于时序数据相关性挖掘的WAMS/SCADA数据融合方法[J].高电压技术,2017,15(4):30-35.
[14]秦圣辉,尤飞,王振华,张云.山火诱发500kV及以上输电线路跳闸事故分析[J].消防科学与技术,2017,36(5):712-716.
[15]宫宇,吕金壮.大数据挖掘分析在电力设备状态评估中的应用[J].南方电网技术,2014,8(6):74-77.