Faculty of Electrical Engineering and Information Technologies

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Author: search.filters.author.Markovska, MarijaHas files: Yes

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    Item type:Publication,
    Classifying Power Quality Disturbances in Noisy Conditions using Machine Learning
    (The Jozhef Stefan Institute, 2019-10)
    Velichkovska, Bojana
    ;
    Markovska, Marija
    ;
    Gjoreski, Hristijan
    ;
    When ensuring high-quality power supply of the power grid it is of the upmost importance to correctly detect and classify any power quality (PQ) disturbance. Selecting the most relevant features is very important in the process of training a genera machine learning model. Therefore, we analyze the power signals and extract information from them, and then select the most significant features. Additionally, an effective classification model is required. In this study we apply grid search throughout the features sets on one side, and the classification algorithms on the side. This way, we determine the most effective combination of an algorithm and feature set for classification of power quality disturbances.
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    Improving the Efficiency of Grounding System Analysis Using GPU Parallelization
    (ETAI - Society for Electronics, Telecommunications, Automatics and Informatics of the Republic of North Macedonia, 2021-09-21)
    Velkovski, Bodan
    ;
    ;
    Gjorgievski, Vladimir
    ;
    Markovska, Marija
    ;
    Grcev, Leonid
    Safety analyses of the effectiveness of large grounding systems are often hampered by the lengthy computation times. Using even the simplest image models, the evaluation of touch and step voltages can require from several minutes to several hours of computations on modern CPUs. Our analysis shows that substantial reduction of computation times can be achieved by utilizing GPU parallelization. In this paper we provide basic steps in the implementation of GPU parallelization on the simplest equipotential model for grounding analysis in homogeneous earth, and we test the effectiveness of this approach in different scenarios.