基于深度学习的电厂电力设备运行状态分析  

Analysis of the Operation State of Power Plant Power Equipment Based on Deep Learning

作　　者：张善 周昊 ZHANG Shan;ZHOU Hao(Zhejiang Zheneng Lanxi Power Generation Co.,Ltd.,Lanxi 321100,China)

机构地区：[1]浙江浙能兰溪发电有限责任公司,浙江兰溪321100

出　　处：《电工技术》2021年第16期66-67,共2页Electric Engineering

摘　　要：为解决传统电厂电力设备运行状态分析残差高的问题,基于深度学习分析电厂电力设备运行状态,通过定义电厂电力设备运行状态变量,基于深度学习表达电厂电力设备运行状态,实现电厂电力设备运行状态分析。实例分析结果表明,该设计方法的分析残差明显低于对照组,能解决传统电厂电力设备运行状态分析残差高的问题。In order to solve the problem of high residual error in the operation status analysis of traditional power plant power equipment,the operation status of power equipment in the power plant is analyzed based on deep learning.By defining the operating state variables of the power equipment of the power plant,the operation state of power plant equipment is learned based on deep learning and the operation state analysis of power plant equipment is realized.The results of case analysis show that the residual error of the design method is significantly lower than that of the control group,which can solve the problem of high residual error of traditional power plant power equipment operation state analysis.

关 键 词：深度学习 运行状态 状态变量 

分 类 号：TP343[自动化与计算机技术—计算机系统结构]