M. Bigdeli,
Volume 18, Issue 1 (3-2022)
Abstract
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)
Abstract
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.
Zahra Memarian, Mahdi Majidi,
Volume 21, Issue 3 (8-2025)
Abstract
This paper presents a two-dimensional (2D) direction of arrival (DOA) estimation method based on the popular correlative interferometer (CI) approach, incorporating practical considerations. Leveraging the flexibility of software-defined radio (SDR) platforms, the proposed array antenna model is designed according to the specifications of a dual-channel synchronous USRP B210 receiver and an appropriate RF switch. To enhance the speed and accuracy of 2D DOA estimation for narrowband, wideband (WB), and frequency hopping (FH) signals, this study introduces a method that integrates power spectrum density (PSD) and spectrogram analysis of the receiver’s instantaneous bandwidth with an optimized filter bank, to precisely detect active frequencies and their intervals. Additionally, a fast, modified K-means clustering algorithm is developed to refine DOA estimation for FH and WB signals across multiple active subchannels. Simulation results demonstrate improved DOA estimation accuracy in multipath conditions, particularly at longer distances, with further enhancements achieved through the proposed clustering method.
