Comparative Study of Advanced Signal Processing Techniques for Islanding Detection in a Hybrid Distributed Generation System


During this paper, islanding detection during a hybrid distributed generation (DG) system is analyzed by the utilization of hyperbolic S-remodel (HST), time-time transform, and mathematical morphology ways. The merits of these strategies are completely compared against commonly adopted wavelet transform (WT) and S-remodel (ST) techniques, as a new contribution to earlier studies. The hybrid DG system consists of photovoltaic and wind energy systems connected to the grid within the IEEE 30-bus system. Negative sequence element of the voltage signal is extracted at the purpose of common coupling and more responsible the above-mentioned techniques. The efficacy of the proposed strategies is also compared by an energy-based technique with correct threshold selection to accurately detect the islanding phenomena. More, to reinforce the accuracy of the result, the classification is completed using support vector machine (SVM) to differentiate islanding from other power quality (PQ) disturbances. The results demonstrate effective performance and feasibility of the proposed techniques for islanding detection below both noise-free and noisy environments, and also in the presence of harmonics.

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