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Summary A novel adaptive terminal sliding mode instantaneous active and reactive power control for both the rotor‐side as well as grid‐side converters of the doubly fed induction generator (DFIG) based wind power extraction system is proposed in this paper using the abc frame of reference. This approach is independent of unmodeled dynamics of the phase‐locked loops that reduces the nonlinearities in computing the control objective. The adaptive nature of the terminal sliding mode controller design offers a better and enhanced transient response as compared with some of the conventional methods for a wide range of disturbances such as switching faults, reference tracking and wind speed variation for both the sub‐synchronous and synchronous modes of operation of the doubly fed induction generator subjected to lower and higher wind speeds. Moreover, a maximum power point tracking algorithm has been incorporated to compute the reference power of the stator of the DFIG, which is utilized in designing the control system for the rotor‐side converter. Further extensive computer simulations have been carried out with the DFIG operating in a single machine or multimachine environment to validate the effectiveness of the proposed control. Also the robustness and stability of the proposed adaptive terminal sliding mode control is verified using the MATLAB/SIMULINK based DFIG model. Copyright © 2015 John Wiley & Sons, Ltd.

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This study presents multi-scale morphological gradient filter (MSMGF) and short-time modified Hilbert transform (STMHT) techniques, respectively, to detect and classify multiclass power system disturbances in a distributed generation (DG)based microgrid environment. The non-stationary power signal samples measured near the target DG's are processed through the proposed MSMGF and STMHT techniques, respectively, and some computations over them generates the target parameter sets. Depending on the complexity of the overlapping in the target attribute values for different disturbance patterns, fuzzy judgment tree structure is incorporated for multiclass event classification, which proves to be robust for most of the classes. In this regard, an extensive simulation on the proposed microgrid models, subjected to a number of multiclass disturbances has been performed in MATLAB/Simulink environment. The faster execution, lower computational burden, superior efficiency as well as better accuracy in multiclass power system disturbance classification by the proposed judgment tree-based MSMGF and STMHT techniques, respectively, as compared to some of the conventional techniques, is significantly illustrated in the performance evaluation section. Further, as illustrated in this section, the real-time capability of the proposed techniques has been verified in the hardware environment, where the results shown are satisfactory.

Summary A new spectral energy differential protection scheme using sparse Fourier kernel fast time‐frequency transform is proposed for the detection, classification, and location of faults either on the grid‐connected or islanded AC microgrid. Initially, the three‐phase average and differential components of the current samples measured on either side of the distribution line are processed through an alteration detection filter, which identifies the fault incipient and consequently registers an alteration index for the particular phase, which identifies the fault. The spectral energy of the differential current components are than computed to classify the type of the fault under a number of intrinsic operating conditions like the meshed and radial architectures and grid‐connected or islanded mode of operation and varying fault distance ratios. Extensive numerical experimentation illustrates satisfactory results for all the cases investigated in this paper, which include detection, classification, and location of faults on the microgrid.