变电站综合自动化系统远动指标统计算法

为了提高变电站综合自动化系统远动指标统计分析能力,需要对变电站综合自动化系统远动指标进行统计处理,提出一种基于模糊聚类和关联规则挖掘的变电站综合自动化系统远动指标统计分析算法。采用分段检验分析方法进行变电站综合自动化系统远动指标的信息采集,提取变电站综合自动化系统远动指标的关联规则特征量,结合模糊融合聚类方法进行变电站综合自动化系统远动指标的大数据聚类处理,采用互信息特征检测方法,进行变电站综合自动化系统远动指标的大数据挖掘和信息检测,根据特征检测结果采用分段模糊聚类方法进行特征归类处理,在聚类空间中实现变电站综合自动化系统远动指标统计分析。仿真结果表明,采用该算法进行变电站综合自动化系统远动指标的统计分析能力较强,大数据聚类性较好,提高了指标统计分析和决策能力。

Statistical algorithm of remote control index for substation integrated automation system

In order to improve the statistical analysis ability of the telecontrol index of the substation integrated automation system,it is necessary to carry on the statistical processing to the substation integrated automation system telecontrol index.Based on fuzzy clustering and association rule mining,a statistical analysis algorithm for telecontrol index of substation integrated automation system is proposed.The method of subsection test and analysis is used to collect the information of telecontrol index of substation integrated automation system,and to extract the characteristic quantity of association rules of the telecontrol index of substation integrated automation system.Combined with fuzzy fusion clustering method,big data clustering processing of telecontrol index of substation integrated automation system is carried out.Mutual information feature detection method is used to excavate telemetric index and detect information of substation integrated automation system.According to the results of feature detection,the feature classification is carried out by using piecewise fuzzy clustering method,and the remote index statistical analysis of substation integrated automation system is realized in clustering space.The simulation results show that the algorithm has better statistical analysis ability and better clustering ability for remote indicators of substation integrated automation system,and improves the statistical analysis and decision-making ability of indicators.