基于大数据分析的电网资产信息评估系统研究

Research on power network asset information evaluation system based on big data analysis

为提高电网资产信息的管理和评估能力,建立电网资产信息评估系统,提出基于大数据分析的电网资产信息评估模型。采用大数据挖掘方法进行电网资产信息挖掘,结合模糊C均值聚类方法进行电网资产信息的特征融合处理,建立电网资源信息分布模型,采用关联特征分解方法进行电网资产信息的自适应重组,实现信息融合滤波检测,运用Lyapunov指数预测方法,实现电网资产信息预测与评估。在Linux内核下进行电网资产信息评估大数据分析算法加载,并在嵌入式环境下进行电网资产信息评估系统优化设计。测试结果表明,该系统进行电网资产信息评估的准确性较高,稳健性较好。

In order to improve the management and evaluation ability of power network asset information, establish the power network asset information evaluation system, In this paper, a power network asset information evaluation model based on big data analysis is put forward ,which uses big data as mining method to mine power network asset information, and combines fuzzy C-means clustering method to deal with the feature fusion of power network assets information. The distribution model of power network resource information is established, the adaptive reorganization of power network asset information is carried out by using the method of correlation characteristic decomposition, the information fusion filter detection is realized, and the Lyapunov exponent prediction method is used. The big data analysis algorithm is loaded under the Linnx kernel, and the optimization design of the power network asset information evaluation system is carried out under the embedded environment. The test results show that, the system has high accuracy and robustness in evaluating power network asset information.