Power grid integration using Kalman filtering

Abstract: Renewable power sources with a relatively uneven or constant DC power production require synchronization methods to work with the current utility power grid. The solution to this synchronization problem has been solved with semiconductor based converters and advanced switching algorithms. To enable switching algorithms that work well with the grids amplitude, phase-shift and frequency, the current waveform has to be measured and estimated.    There are many sources of noise that will add distortion of the current waveform, making its appearance less similar to the grids. The distorted measurement affects the accuracy of the converters negatively. Therefore, using a filter algorithm to attenuate the grid noise is required.  This project uses a Kalman filter with the aim to decrease the noise and estimate the current phase shift for a three phase power-grid.  To achieve reliable and fast calculation, implementing the Kalman filter within a FPGA were done.The project contains results from both simulated MATLAB data and the FPGAs real time data. The method was able to estimate the grid within a few Hz frequency deviation and enable some noise reduction. For larger degree of harmonic distortion during steady state operation, the Kalman filter could remove more of the harmonic distortion. Limits and differences with MATLAB are discussed for the FPGA implemented Kalman filter.