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Showing 2 results for K-Means

M. Bigdeli,
Volume 18, Issue 1 (3-2022)

Moisture in the transformer insulation can shorten its life. There are many methods for detecting humidity in transformer paper insulation. One of the methods used in the factory to evaluate the drying process of transformer insulation and determine its humidity is the frequency response analysis method. In this paper, the desired experiments are performed on different transformers, and after obtaining the results of frequency response measurements, the required features are extracted from them. Then, using the k-means method, these features are placed in three clusters (dry, wet, and excessively wet). The cost function of the k-means method is optimized using the particle swarm optimization (PSO) algorithm to get a better result. By applying new data from different transformers, the capability of the proposed method in determining the moisture content of the transformer is evaluated. The results obtained from the evaluation of the insulation condition of another group of transformers indicate the high accuracy of the proposed method.

Y. Fattahyan, N. Ramezani, I. Ahmadi,
Volume 18, Issue 3 (9-2022)

Using doubly-fed induction generator (DFIG) based onshore wind farms in power systems may lead to mal-operation of the second zone (Z2) of distance protection due to the uncertain number of available wind turbines on the one hand and the function of DFIGs control system to maintain the bus voltage on the other hand. In such cases, variable injected current by the wind farm causes distance relay fall in trouble to distinguish whether the fault point is in the Z2 operating area or not. In the current study, an adaptive settings scheme is proposed to determine the Z2 setting value of distance relays for such cases. The proposed method is based on the adaptive approach and the settings group facility of the commercial relays. The proposed method applies the k-means clustering approach to decrease the number of setting values calculated by the adaptive approach to the number of applicable settings group in the distance relay and uses the Particle Swarm Optimization (PSO) algorithms to achieve the optimum setting values. The high accuracy of the proposed method in comparison with other methods, suggested in the literatures, is shown by applying them to the IEEE 14-bus grid.

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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.