电力系统保护与控制
電力繫統保護與控製
전력계통보호여공제
POWER SYSTM PROTECTION AND CONTROL
2013年
21期
38-45
,共8页
电力系统%故障诊断%衰减径向基函数神经网络%容错性%鲁棒性
電力繫統%故障診斷%衰減徑嚮基函數神經網絡%容錯性%魯棒性
전력계통%고장진단%쇠감경향기함수신경망락%용착성%로봉성
power system%fault diagnosis%decay radial basis function neural network%fault-tolerance%robustness
为提高电网故障诊断神经网络模型的构建速度，提出了一种基于多输出衰减径向基函数（Multi-output Decay Radial Basis Function, MDRBF）神经网络的故障诊断方法。DRBF神经网络不需训练即能以任意精度一致逼近任意连续多变量函数。介绍了单输出DRBF（Single-output DRBF, SDRBF）神经网络，分析了其存在的不足，即只能处理单输出变量问题，不能直接应用于电网故障诊断。在此基础上，根据电网元件的故障特点，提出了将SDRBF神经网络演变为多输出DRBF（Multi-Output DRBF, MDRBF）神经网络的拓展策略，以满足电网故障诊断的多输出变量需求。以4母线输电网络作为仿真系统，算例结果表明，该方法具有实现简单、容错性好、鲁棒性强等特点。
為提高電網故障診斷神經網絡模型的構建速度，提齣瞭一種基于多輸齣衰減徑嚮基函數（Multi-output Decay Radial Basis Function, MDRBF）神經網絡的故障診斷方法。DRBF神經網絡不需訓練即能以任意精度一緻逼近任意連續多變量函數。介紹瞭單輸齣DRBF（Single-output DRBF, SDRBF）神經網絡，分析瞭其存在的不足，即隻能處理單輸齣變量問題，不能直接應用于電網故障診斷。在此基礎上，根據電網元件的故障特點，提齣瞭將SDRBF神經網絡縯變為多輸齣DRBF（Multi-Output DRBF, MDRBF）神經網絡的拓展策略，以滿足電網故障診斷的多輸齣變量需求。以4母線輸電網絡作為倣真繫統，算例結果錶明，該方法具有實現簡單、容錯性好、魯棒性彊等特點。
위제고전망고장진단신경망락모형적구건속도，제출료일충기우다수출쇠감경향기함수（Multi-output Decay Radial Basis Function, MDRBF）신경망락적고장진단방법。DRBF신경망락불수훈련즉능이임의정도일치핍근임의련속다변량함수。개소료단수출DRBF（Single-output DRBF, SDRBF）신경망락，분석료기존재적불족，즉지능처리단수출변량문제，불능직접응용우전망고장진단。재차기출상，근거전망원건적고장특점，제출료장SDRBF신경망락연변위다수출DRBF（Multi-Output DRBF, MDRBF）신경망락적탁전책략，이만족전망고장진단적다수출변량수구。이4모선수전망락작위방진계통，산례결과표명，해방법구유실현간단、용착성호、로봉성강등특점。
To improve the rate of construction of neural network based model of power grids fault diagnosis, a method based on multi-output decay radial basis function (MDRBF) neural network for fault diagnosis is proposed. DBRF neural network can uniformly approximate any continuous multivariate functions with arbitrary precision without training. The single-output DRBF (SDRBF) neural network is introduced, and its shortage in fault diagnosis of power grids is analyzed. Since single-output DRBF (SDRBF) neural network can only solve the single-variable output problem, therefore, it can not be used directly in fault diagnosis of power grids. On this basis, a strategy for expanding the SDRBF neural network to the MDRBF neural network is proposed according to the fault characteristic of electric components. MDRBF neural network is able to satisfy the multi-variable output need of fault diagnosis of power grids. A four-bus transmission grid is adopted as a simulation system and the results show that the proposed diagnostic method based on MDRBF neural network is simple and has good fault-tolerance and strong robustness.
