基于神經網絡的電力系統狀態估計

基于神經網絡的電力系統狀態估計①

韓富春 　王娟娟

（太原理工大學電氣與動力工程學院　太原　030024）

    摘  要　本文以Tank和Hopfield神經網絡為基礎，建立了一種由主從網絡構成的電力系統狀態估計神經網絡模型。理論分析和實例模擬結果表明：該網絡是穩定的，該方法是可行有效的。
    關鍵詞　狀態估計　電力系統　神經網絡

1　INTRODUCTION
　　Among the current state estimators，due togood estimation qualities and astringency，weightedleast estimator is a classical algorithm and an aca－demic basis．Butit also has some shortcomingssuchas the calculation of matrices．The paper applies aneural network modelto solve the real－time leastsquares（RLS）problem．Theoretical analysis andsimulations prove that this network is very suitableto solve this kind of problem and has greatly im－proved on the traditionalpower state estimation al－gorithm．
2　A MODEL OF WEIGHTED LEAST SQUARESALOGORITHM
    The observation equation ofpower systemstate estimation is nonlinear and can be linear as:
    z＝Hx＋v   （1）
where x isan dimension state vector；z isa mdimen－sion measurement vector；v is a measurement errorvector，which is normalized as：H is a m×n dimension observation matrix．Rank［H］＝n．Its elements are decided by the structureof power system and the configuration of meteringsystem．In general case，H can act as constant be－cause its change is minute in every iteration．
　　The observation function applying weightedleastsquares algorithmis：

where R－1 is weight，Δz is the difference betweenthe measurementand the value ofthe correspondingmeasurementfunction．Eq．（2）is expressed in a vec－
tor form：

3　THEREALIZATION OFRLSALGO-RITHM USINGANEURALNETWORK
    According to the reference[3]that a energy function was used to research the stability of a feed－back neuralnetwork and simulation electroniccircuitcould realize its circuitmodel．In reference［1］，thereis a network that comprised of a main and a sub－sidiary network，showed as the Figure 1．The paperapplies the network to power system state estima－tion successfully．The main and the subsidiary neu－rons are connected with each other．The left mainnetwork has n neurons，every neuron is modeled asan amplifier，and the relation ofitsinput and outputis nonlinear．It has input capacitance Ci and resis－tance Ri．vi（t）and ui（t）are the i－th neuron output and input voltage．g（u）is a degressive function．

[1] [2] [3] 下一頁

　　湖南省陽光電子技術學校常年面向全國招生.安置就業。考試合格頒發全國通用權威證書：《中華人民共和國職業資格證》 、《電工證》 、《焊工證》 。采用我校多年來獨創的“模塊教學法”,理論與實踐相結合、原理＋圖紙＋機器三位一體的教學模式，半天理論，半天實踐，通俗易懂，確保無任何基礎者也能全面掌握維修技能、成為同行業中的佼佼者。工作(一期不會，免費學會為止)。