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基于大数据分析的智能电网变电站运维优化研究
集成电路应用
叶雪峰
国网赣州供电公司
摘要: 随着智能电网建设的深入推进,变电站运维管理面临设备规模持续扩大,运行数据快速增长与传统人工运维效率不足等多重压力,大数据分析技术为变电站运维提供了新的技术路径,其通过对多源异构运行数据的系统采集、深度挖掘与智能建模,能够实现设备状态精准感知、故障提前预警及运维资源合理调配。以某省级电网典型220 kV变电站为实验对象,构建基于大数据平台的运维优化系统,该研究对设备健康评估准确率、故障预警及时率、运维调度效率等关键指标进行量化分析,实验结果表明,引入大数据分析方法后设备故障预警准确率提升至93.1%,运维综合成本降低约18.3%,巡检响应效率显著改善,验证了大数据技术在变电站运维优化中的有效性与可行性。
中图分类号:TM63;TM76文献标识码:ADOI:10.19339/j.issn.1674-2583.2026.05.005
中文引用格式:叶雪峰. 基于大数据分析的智能电网变电站运维优化研究[J].集成电路应用,2026,43(5):36-39.
英文引用格式:Ye Xuefeng. Research on optimization of smart grid substation operation and maintenance based on big data analysis[J].Application of IC,2026,43(5):36-39.
Research on optimization of smart grid substation operation and maintenance based on big data analysis
Ye Xuefeng
State Grid Ganzhou Power Supply Company
Abstract: With the deepening of smart grid construction, substation operation and maintenance management is facing multiple pressures such as the continuous expansion of equipment scale, massive growth of operating data, and insufficient efficiency of traditional manual operation and maintenance. Big data analysis technology provides a new technical path for substation operation and maintenance. Through systematic collection, deep mining, and intelligent modeling of multi-source heterogeneous operating data, it can achieve accurate perception of equipment status, early warning of faults, and rational allocation of operation and maintenance resources. Taking a typical 220 kV substation in a provincial power grid as the experimental object, a big data platform-based operation and maintenance optimization system is constructed to quantitatively analyze key indicators such as equipment health assessment accuracy, fault warning timeliness, together with operation and maintenance scheduling efficiency.
Key words : big data analysis; smart grid; substation operation and maintenance; equipment status monitoring; fault warning

引言

智能电网是现代电力系统转型升级的核心方向,变电站作为电网能量转换与调配的关键节点,其运维水平直接影响供电可靠性与系统整体安全。当前,变电站设备类型日趋多样,运行环境日益复杂,历史积累的运行数据体量庞大,传统依赖人工巡检与经验判断的运维模式已难以满足精细化、主动化管理的现实需求[1]。大数据技术凭借在数据整合、规律挖掘与智能决策方面的独特优势,为破解上述困境提供了有效支撑,使变电站运维管理从被动应急响应向主动预防预控转变成为可能。本文依托真实电网运行数据,系统探索大数据分析方法在变电站设备监测、故障诊断与运维调度中的作用机制,以期为提升变电站智能化运维管理水平提供理论依据与实践参考[2]。


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作者信息:

叶雪峰

(国网赣州供电公司,江西赣州341500)

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