Programmable logic design of a compact Genetic Algorithm for phasor estimation in real-time

Abstract The main objective of this work is to present an efficient method for phasor estimation based on a compact Genetic Algorithm (cGA) implemented in Field Programmable Gate Array (FPGA). To validate the proposed method, an Electrical Power System (EPS) simulated by the Alternative Transients Program (ATP) provides data to be used by the cGA. This data is as close as possible to the actual data provided by the EPS. Real life situations such as islanding, sudden load increase and permanent faults were considered. The implementation aims to take advantage of the inherent parallelism in Genetic Algorithms in a compact and optimized way, making them an attractive option for practical applications in real-time estimations concerning Phasor Measurement Units (PMUs).

[1]  Paolo Castello,et al.  Impact of the Model on the Accuracy of Synchrophasor Measurement , 2012, IEEE Transactions on Instrumentation and Measurement.

[2]  A.G. Phadke,et al.  Exploring the IEEE Standard C37.118–2005 Synchrophasors for Power Systems , 2008, IEEE Transactions on Power Delivery.

[3]  Paolo Attilio Pegoraro,et al.  Performance comparison of algorithms for synchrophasors measurements under dynamic conditions , 2011, 2011 IEEE International Workshop on Applied Measurements for Power Systems (AMPS).

[4]  Boon-Teck Ooi,et al.  Application of Enhanced Phase-Locked Loop System to the Computation of Synchrophasors , 2011, IEEE Transactions on Power Delivery.

[5]  S. Maestri,et al.  Variable Sampling Period Filter PLL for Distorted Three-Phase Systems , 2012, IEEE Transactions on Power Electronics.

[6]  José Antonio de la O. Serna,et al.  Dynamic Phasor Estimates for Power System Oscillations , 2007, IEEE Transactions on Instrumentation and Measurement.

[7]  D. Petri,et al.  Accuracy of the synchrophasor estimator provided by the interpolated DFT algorithm , 2012, 2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings.

[8]  J. Thorp,et al.  A New Measurement Technique for Tracking Voltage Phasors, Local System Frequency, and Rate of Change of Frequency , 1983, IEEE Transactions on Power Apparatus and Systems.

[9]  J. A. de la O Serna,et al.  Instantaneous Oscillating Phasor Estimates With Taylor$^K$-Kalman Filters , 2011, IEEE Transactions on Power Systems.

[10]  S. N. Sivanandam,et al.  Introduction to genetic algorithms , 2007 .

[11]  A.G. Phadke,et al.  Synchronized phasor measurements in power systems , 1993, IEEE Computer Applications in Power.

[12]  David E. Goldberg,et al.  The compact genetic algorithm , 1999, IEEE Trans. Evol. Comput..

[13]  M. Kezunovic,et al.  Real-Time Power System Frequency and Phasors Estimation Using Recursive Wavelet Transform , 2011, IEEE Transactions on Power Delivery.

[14]  G. M. Burt,et al.  P and M Class Phasor Measurement Unit Algorithms Using Adaptive Cascaded Filters , 2013, IEEE Transactions on Power Delivery.

[15]  Aurobinda Routray,et al.  A novel Kalman filter for frequency estimation of distorted signals in power systems , 2002, IEEE Trans. Instrum. Meas..

[16]  Dario Petri,et al.  Synchrophasor Estimators Accuracy: A Comparative Analysis , 2013, IEEE Transactions on Instrumentation and Measurement.

[17]  David E. Goldberg,et al.  The Design of Innovation: Lessons from and for Competent Genetic Algorithms , 2002 .

[18]  Jack E. Volder.  The Birth of Cordic , 2000, J. VLSI Signal Process..

[19]  Alexandre C. B. Delbem,et al.  Genetic algorithms applied to phasor estimation and frequency tracking in PMU development , 2013 .

[20]  T. Sidhu,et al.  A new half-cycle phasor estimation algorithm , 2005, IEEE Transactions on Power Delivery.

[21]  David G. Hart,et al.  PMUs - A new approach to power network monitoring , 2001 .

[22]  José Antonio de la O. Serna,et al.  Dynamic Phasor and Frequency Estimates Through Maximally Flat Differentiators , 2010, IEEE Transactions on Instrumentation and Measurement.

[23]  José Antonio de la O. Serna,et al.  Dynamic Harmonic Analysis Through Taylor–Fourier Transform , 2011, IEEE Transactions on Instrumentation and Measurement.

[24]  Joe-Air Jiang,et al.  A Full- and Half-Cycle DFT-based technique for fault current filtering , 2010, 2010 IEEE International Conference on Industrial Technology.

[25]  Alexandre C. B. Delbem,et al.  Frequency Estimation Using a Genetic Algorithm With Regularization Implemented in FPGAs , 2012, IEEE Transactions on Smart Grid.

[26]  T.T. Nguyen,et al.  A fast and accurate method for estimating power systems phasors using DFT with interpolation , 2006, 2006 IEEE Power Engineering Society General Meeting.

[27]  Magnus Akke,et al.  Sample Value Adjustment Improves Phasor Estimation at Off-Nominal Frequencies , 2010, IEEE Transactions on Power Delivery.

[28]  M. Karimi-Ghartemani,et al.  Robust and frequency-adaptive measurement of peak value , 2004, IEEE Transactions on Power Delivery.