Two-Stage Improved Recursive Newton-Type Algorithm for Power-Quality Indices Estimation

In the paper, a new improved recursive Newton-type algorithm (IRNTA) suitable for various measurement applications in the electric power systems is presented. Here, it is applied for power-quality (PQ) indices estimation according to the IEEE Standard 1459-2000. Basically, the algorithm is a recursive nonlinear estimator, improved with a strategy of sequentially tuning the forgetting factor. This approach generally improves the algorithm performance: immunity to random noise, accuracy, and the speed of convergence. The IRNTA considers the power frequency as an unknown model parameter and takes into account distortion of voltages and currents. Therefore, it is suitable for the real-time PQ monitoring. The algorithm has two stages. In the first stage, the input signal spectra and fundamental frequency are estimated, whereas in the second stage, the unknown PQ indices are calculated. To demonstrate the efficiency of the proposed algorithm, the results of computer simulations and laboratory testing are presented.