4350

225 دكتري

دكتري

برق

اصفهان: دانشگاه صنعتي اصفهان، دانشكده برق و كامپيوتر

1387

يازده، 220، [II]ص.: مصور، جدول، نمودار

ص.ع. به: فارسي و انگليسي

محمداسماعيل همداني گلشن

فريد شيخ الاسلام، صفيه محمودي

14/12/87

حميدرضا كارشناس

مهندسي برق و كامپيوتر

ID225 دكتري

به فارسي و انگليسي: قابل رؤيت در نسخه ديجيتال

AbstractThe time varying nature of electric arc furnace EAF gives rise to voltage fluctuations whichproduce the effect known as flicker The ability of static VAr compensator SVC a widelyused method for flicker reduction is limited by delays in reactive power measurements andthyristor ignition To improve the SVC performance in flicker compensation arc furnacereactive power can be predicted for a half cycle ahead by using a suitable dynamic model forEAF To obtain suitable models for EAFs reactive power this thesis uses huge field dataincluding voltages and currents for eight EAFs installed in Mobarakeh Steel Industry Thereactive power times series are produced from the recorded currents and voltages based on thefundamental reactive power A novel and comprehensive study including linear analysis online calculation of models coefficients and non linear analysis is performed for dynamicmodeling of arc furnace reactive power variation In the linear analysis ARMA models areused for reactive power time series and appropriate orders of ARMA models are obtained byperforming various statistical tests The results show that reactive power times series with 10sec length are stationary and can be suitably modeled by ARMA 2 1 ARMA 2 2 andARMA 3 2 models In this analysis vector ARMA models are also investigated The betterperformance of the compensator in the case of employing predicted reactive power of EAF isdemonstrated rather than that of the conventional method by using three new indices that aredefined based on concepts of flicker frequencies and the power spectral density It is shownthat the EAF reactive power models coefficients and their variations are different from onedata record to another and do not follow any specific law Therefore it is necessary to updatethe model coefficients for prediction purposes For this purpose the transient and steady stateperformances of NLMS RLS and online genetic methods are studied based of new indices Inthe nonlinear analyses non linear parameters of the reactive power time series are obtained Then by using different tests it is demonstrated that the percent of time series that havenonlinear properties is between 20 to 60 for different tests In addition by study ofmaximum lyapanov exponent it is found that reactive power time series are not chaoticprocess Finally by using a new method based on the residual time series and some newindices it is demonstrated that the ratio of time series nonlinear deterministic component totheir deterministic component is negligible and the nonlinear deterministic component of thetime series can be ignored in the prediction of arc furnace reactive power

محمداسماعيل همداني گلشن

فريد شيخ الاسلام، صفيه محمودي

حميدرضا كارشناس