Methods for Identification of Instantaneous Frequencies for Application in Isolated Microgrid
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THE introduction of new methods for production and distribution of electrical energyhas increased the attention related to problems with power quality and the presenceof time-varying frequencies. It has been reported several cases with such problems in isolated electrical systems such as isolated microgrids for incorporation of renewable energysources and marine vessel power systems. The sources and loads in such systems are usuallyinterfaced with power electronic equipment, meaning that there is low or no inertia.The low inertia and the stochastic nature of the generation and loads results in systemsthat are prone to nonlinear distortions and variations in the fundamental frequency. Thehitherto used measurement- and monitoring equipment have mostly been based on averagevalue calculation. The aforementioned problems in isolated electrical systems have madethe need of measurement of instantaneous values instead of average values apparent, inorder to have monitoring- and control systems with satisfying performance and accuracy. This thesis studies the use of several types of Kalman filters (KF), Hilbert-Huang Transform(HHT) and the proposed method of merging empirical mode decomposition (EMD) and KF for the purpose of tracking instantaneous values of voltage- and current waveforms in isolated microgrids with the aforementioned challenges. Both synthetic signals and realmeasurements from a marine vessel power system were used to validate the methods. Thealgorithms and methods were implemented in Matlab and Simulink. In varying degrees, the methods did all prove to be viable options for tracking of the fundamental frequency on the marine vessel. The proposed method turned out to be particularlypowerful to decompose multicomponent signals consisting of several time-varying monocomponents, and track their instantaneous amplitude and frequency.