计算机技术与发展2017，Vol.27Issue(4)：164-169,6.DOI:10.3969/j.issn.1673-629X.2017.04.037
基于耦合隐马尔可夫模型的输电线路状态评估
State Evaluation of Transmission Line Based on CoupledHidden Markov Model
摘要
Abstract
Overhead transmission line is an important part of the transmission network.The running state will directly affect the reliability of the operation of the whole power system.In order to learn the running state of the transmission line exactly,it is needed to evaluate the line accurately.A machine learning method based on artificial intelligence called Coupled Coupled Hidden Markov Model (CHMM) has been proposed for the assessment of the state of the overhead transmission line.According to the assessment demand,the historical assessment data of overhead transmission line under normal,abnormal,attention,serious four kinds of state are collected,and the data are normalized.The artificial intelligence algorithm is used to train the normalized four kinds of data to obtain the model parameters of the four groups and four states have been established for the CHMM.The normalized test data are brought into the four sets of models,and the four state evaluation values are obtained,in which the maximum value of the model is the state of the test data.This machine learning model is applied to conduct the empirical analysis and an overhead transmission line is evaluated,compared with the result of the assessment and the actual monitoring.The result of analysis and estimation shows that the method is effective and feasible.关键词
人工智能/机器学习/耦合隐马尔可夫模型/状态评估Key words
artificial intelligence/machine learning/coupled hidden Markov model/state evaluation分类
信息技术与安全科学引用本文复制引用
葛夕武,朱超,马骏毅,刘强,梁晟杰,吴国梁..基于耦合隐马尔可夫模型的输电线路状态评估[J].计算机技术与发展,2017,27(4):164-169,6.基金项目
国家电网公司总部科技项目(PD71-14-041) （PD71-14-041）
