Search for dissertations about: "machine learning power quality"

Showing result 1 - 5 of 28 swedish dissertations containing the words machine learning power quality.

  2. 1. Artificial Intelligence-Based Characterization and Classification Methods for Power Quality Data Analytics

    Author : Azam Bagheri; Math Bollen; Surya Santoso; Luleå tekniska universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Power System; power Quality; Voltage Dip; Big Data; Deep Learning; Machine Learning; Active Learning; Consensus Contriol; Electric Power Engineering; Elkraftteknik;

    Abstract : One of the important developments in the electric power system is the fast increasing amount of data. An example of such data is formed by the voltages and currents coming from power-quality measurements. READ MORE

  4. 2. Applications of Unsupervised Deep Learning for Analysing Time-Varying Power Quality Big Data

    Author : Roger Alves de Oliveira; Math Bollen; Sarah Rönnberg; Matti Lehtonen; Luleå tekniska universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; power quality; power system harmonics; electric power distribution; interharmonics; big data analytics; pattern analysis; unsupervised learning; deep learning; artificial intelligence; geomagnetically induced currents; Electric Power Engineering; Elkraftteknik;

    Abstract : Continuous power quality monitoring allows grid stakeholders to obtain information about the performance of the network and costumer facilities. Moreover, the analysis of continuous monitoring allows researchers to obtain knowledge on power quality phenomena. Power quality measurements result in a large amount of data. READ MORE

  5. 3. On Deep Machine Learning Based Techniques for Electric Power Systems

    Author : Ebrahim Balouji; Chalmers tekniska högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Deep Learning; Cable faults; phase locked loop; Flicker; Harmonics and Interharmonics; Reinforcement learning; Voltage Dip; Active Power filter; Machine Learning; Voltage fluctuation; Partial Discharges;

    Abstract : This thesis provides deep machine learning-based solutions to real-time mitigation of power quality disturbances such as flicker, voltage dips, frequency deviations, harmonics, and interharmonics using active power filters (APF). In an APF the processing delays reduce the performance when the disturbance to be mitigated is tima varying. READ MORE

  6. 4. Synthetic data for visual machine learning : A data-centric approach

    Author : Apostolia Tsirikoglou; Jonas Unger; Gabriel Eilertsen; Anders Ynnerman; Philipp Slusallek; Linköpings universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Training data; Synthetic images; Computer graphics; Generative modeling; Natural images; Histopathology; Digital pathology; Machine learning; Deep learning;

    Abstract : Deep learning allows computers to learn from observations, or else training data. Successful application development requires skills in neural network design, adequate computational resources, and a training data distribution that covers the application do-main. READ MORE

  7. 5. Data-driven quality management using explainable machine learning and adaptive control limits

    Author : Niklas Fries; Patrik Rydén; Jun Yu; Rebecka Jörnsten; Umeå universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; quality management; machine learning; local explanation methods; process adjustment policies; simulation; matematisk statistik; Mathematical Statistics; data science; data science;

    Abstract : In industrial applications, the objective of statistical quality management is to achieve quality guarantees through the efficient and effective application of statistical methods. Historically, quality management has been characterized by a systematic monitoring of critical quality characteristics, accompanied by manual and experience-based root cause analysis in case of an observed decline in quality. READ MORE