شناسايي مشخّصات مودهاي نوساني سيستم قدرت به كمك واحدهاي اندازه گيري فازوري

چكيده انگليسي :

Identification of Power System Oscillation Modes Characteristics with Phasor Measurement Units Farzad Dalavi dalavi farzad@ec iut ac ir August 26 2020 Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156 83111 IranDegree Master of Science Language FarsiSupervisor M E Hamedani Golshan Prof hgolshan@cc iut ac ir AbstractWith increasing electrical energy demand and loading of transmission lines inter area oscillations within a frequencyrange of 0 2 to 0 8 Hz are more obvious in modern power systems which are the most important reason for oscil latory rotor angle instability When inter area modes are excited the power system is divided into areas in whichgenerators at each area are coherent but they are anti phase oscillation respect to other generator groups The inter area oscillations have a lower frequency and damping ratio than local modes and they cause power oscillation attie lines between areas that restricts the power transmission capacity Therefore online monitoring and control ofinter area modes are vital for secure and reliable operation of the power system With the recent advancement of thetechnology and the emergence of wide area measurement systems WAMSs and the possibility of measure phasorquantities using phasor measurement units PMUs the dynamic response of power system can be online moni tored using data analysis and signal processing techniques The main feature of signal processing techniques is thatthey don t need any knowledge about the power system order or power equipment models In this thesis a hybridmethod based on WAMS for the detection of dominant inter area oscillation modes and evaluation of generatorsoscillation patterns at each considerable mode is proposed The proposed method can also detect the most efficientdamping controller loops for improving the damping of dominant oscillation modes The proposed method usesthe empirical mode decomposition EMD algorithm and correlation analysis CA technique In the first step thefrequency components of measured signals are decomposed from highest to lowest frequency by the EMD algorithmand then the instantaneous frequency characteristics of each extracted component are calculated by hilbert huangtransform HHT Power system oscillation modes are identified by comparing the frequency averages with the typ ical frequency range of low frequency electromechanical oscillations LFEOs and finally the dominant oscillationmodes are determined by comparing the instantaneous energy level of oscillation modes One feature of the EMDalgorithm is the ability to extract waveforms of oscillation modes Considering dominant mode waveforms as theinput for correlation analysis it can determine how generators oscillate against each other by calculating the phasedifference between signals Furthermore efficient feedback signals can be determined by estimation relative magni tude of mode shape or right eigenvectors Moreover by comparing left eigenvectors magnitudes efficient dampingcontrollers can be specified In other words the efficient damping controller loops based on observability and con trollability concepts related to right and left eigenvectors can be identified The applicability of the proposed methodin this thesis is demonstrated by several analyses and simulations on IEEE 9 bus and IEEE 39 bus test systems KeywordsInter Area Oscillations Phasor Measurement Unit PMU Empirical Mode Decomposition EMD Algorithm Cor relation Analysis CA Mode Shape Wide Area Damping Controller WADC

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شناسايي مشخّصات مودهاي نوساني سيستم قدرت به كمك واحدهاي اندازه گيري فازوري

نوسانات بين ناحيه اي , واحدهاي اندازه گيري فازوري , الگوريتم روش تجربي تجريه سيگنال به توابع مُود ذاتي , تحليل همبستگي , صورت مُود , كنترل كننده ميراساز ناحيه گسترده