机器学习在电力系统故障中的运用

Application of Machine Learning in Power System Failure

近年来,由于人们用电负荷量的增加,电力系统故障的不可预测性、不可控性也逐渐增大。随着大数据技术的迅速发展,机器学习被广泛应用于各个领域,发挥着不可或缺的作用,其自身的优势也越来越明显。电力行业在不断发展中积累了大量的数据,因此主要介绍了几种常见的电力系统故障,系统分析了通过建立机器学习算法模型对电力系统异常数据进行检测的方法,找出故障发生的位置,并对故障点进行预测,以达到电力系统故障诊断的目的。

In recent years,due to the increase of people's power load,the unpredictability and uncontrollability of power system failures also increase gradually.With the rapid development of big data technology,machine learning is widely used in various fields,playing an indispensable role,its own advantages are becoming more and more obvious.In the continuous development of power industry,as well as accumulated a large amount of data,mainly introduces several kinds of common fault in power system,the system analysis of the model how to through the establishment of machine learning algorithm to detect abnormal data in power system,find out the fault location,and to forecast the point of failure,in order to achieve the purpose of the power system fault diagnosis.