Synchrophasor Estimation Algorithm And Its Optimization Using Artificial Bee Colony Algorithm

Phasor Measurement units(PMU)is one of most emerging technology.PMU provides time stamped measurements of voltage and current that’s why true picture of power system is obtained.In short we can say that Phasor measurement Units are playing fundamental role in analysis control and security of power system.Main focus of my research work is selection of appropriate algorithm based on dynamic model used by PMU for Synchrophasor estimation and the optimization of selected Synchrophasor estimation algorithm using Artificial Bee Colony is used.Need of design of dynamic model arises because real power system experiences oscillations and transients in case of switching operations and faults so static Phasor is insufficient to monitor dynamic power system.First of all,dynamic model is designed to analyze dynamic behavior of power system in case of faults,switching operations and transients.Conventional Discrete Fourier Transform(DFT)cannot use for Phasor estimation because averaging effect of DFT only removes spectral leakage caused by harmonics that are integer multiples of fundamental frequency.Spectral leakage caused by inter harmonics could not be removed by conventional DFT.This specific problem is successfully fixed by making improved DFT with Digital filter.Cut off frequency of digital filter is allowed to pass specific frequencies in this way PMU gets immunity to out of band signals.Dynamic Synchrophasor is successfully approximated by 2nd order Taylor series.Linear relationship between 2nd order coefficients of Taylor series and error due to averaging effect of DFT is explored using weighted least Square approach.Due to this linear relationship error caused by raw measurement is minimized.Artificial Bee Colony Algorithm is applied on digital filter to optimize it.Artificial Bee Colony Algorithm is used because it is simple,its robustness is strong,stochastic nature it can easily combined with other methods,few control parameters and convergence is fast.FIR filter is designed using Hamming window coefficientS.ABC algorithm is used to reduce mean square error while updating hamming window coefficients.IEEE Std.C37.118.1-2011 which consists of series of steady state and dynamics tests is used to investigate performance of optimal filter.Step change and dynamic test such as ramp,magnitude and phase angel modulation are conducted to check behavior of optimal filter.Total Vector error is calculated after each test and compared to error before optimization numerical values and graphs proved that error after optimization is significantly reduced then error before optimization.Optimal Filter is successfully estimated amplitude,Phasor,frequency and ROCOF.