M.K.K. Alabdullh; M. Joorabian; S.G. Seifossadat; M. Saniei
Abstract
Transformers are one of the most important parts of the electric transmission and distribution networks, and their performance directly affects the reliability and stability of the grid. Maintenance and replacing the faulted transformers could be time-consuming and costly and accordingly, a solution ...
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Transformers are one of the most important parts of the electric transmission and distribution networks, and their performance directly affects the reliability and stability of the grid. Maintenance and replacing the faulted transformers could be time-consuming and costly and accordingly, a solution should be proposed to prevent it. This led to studies in the field of transformer lifetime management. As a result, estimating the remaining lifetime of the transformer is a crucial part for the mentioned solution. Therefore, this paper aims to tackle this issue through employing a new algorithm to estimate the lifetime of a transformer by combining selection methods and Artificial Intelligence (AI)-based techniques. The main goal of this method is to reduce the estimation error and estimation time simultaneously. The proposed approach assesses transformers based on environmental conditions, power quality, oil quality, and dissolved gas analysis (DGA). Consideration of additional factors overcomes the disadvantage of traditional methods and gives a meticulous result. In this respect, the collected data from the power transformer of Iran and Iraq as well as regions with different conditions are employed in the studied algorithm. Several combinations of algorithms are investigated to choose the best one. Principal Component Analysis (PCA) is employed in the next step for weighing the various parameters to improve the accuracy and decrease execution time. Results show that the Bayesian neural network provides the best performance in the predicting remaining lifetime of the transformer with an accuracy about 98.4%.
M. Abasi; M. Joorabian; A. Saffarian; S.G. Seifossadat
Abstract
Fault location in transmission lines compensated by flexible alternating current transmission system (FACTS) devices and series capacitor (SC) compensators is much more complicated than simple lines due to the presence of time-variant voltage and current sources in the topology of transmission lines. ...
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Fault location in transmission lines compensated by flexible alternating current transmission system (FACTS) devices and series capacitor (SC) compensators is much more complicated than simple lines due to the presence of time-variant voltage and current sources in the topology of transmission lines. In recent years, due to the increasing presence of reactive power compensators in power systems and the researchers’ desire to study the presence of such equipment in the network, many articles have been published in the field of fault location in transmission lines equipped with reactive power compensators. Thus, the fault location problem in electrical power transmission lines equipped with reactive power compensators, including FACTS and SC devices, is comprehensively discussed and analyzed in this paper. For the first time, all the basic indices and factors that have always been very effective in analyzing the fault location problem in transmission lines equipped with reactive power compensators in various papers are classified thoroughly. Then, based on the types of reactive power compensators, all the literature published in the field of fault location in compensated transmission lines are categorized. Finally, a comparison table is presented to examine the fundamental indices of the literature in this field.
