Empirical Investigations: Power Quality Disturbance Classification


Abstract views: 42 / PDF downloads: 66

Authors

  • Sıtkı AKKAYA Sivas University of Science and Technology

DOI:

https://doi.org/10.59287/icaens.1014

Keywords:

ower Quality Disturbances, Experimental Setup, Classification, IEEE 1159, IEEE 1459

Abstract

In electrical power systems, one of the most essential parameters is a system signal with stable fundamental amplitude and frequency. Some disturbances have a negative impact on this stability, yet. These disturbances, known as power quality disturbances (PQDs), encompass phenomena such as sag, interruption, swell, harmonics, flicker, interharmonics, spike, notch, and transients. PQDs can arise individually or in some combinations. They pose unpredictable and variable effects on system components giving rise to destructive outcomes. Acquisition of real-world datasets related to these disturbances is challenging due to the randomness and complex nature of power systems. Therefore, the importance of conducting experimental studies to investigate and analyze PQDs has significantly increased. This study aims to serve as a valuable resource for researchers investigating PQDs. It provides a guidance, offering insights into some types of PQDs and their characteristics. This paper supports researchers in understanding and addressing the challenges based on PQDs by presenting knowledge about these disturbances and their impacts. Recognizing the significance of experimental studies, the compilation includes methodologies, experimental setups, and tools employed for studying PQDs. It emphasizes the necessity for experimental datasets to enhance research in this field and highlights the importance of PQD investigation.

Author Biography

Sıtkı AKKAYA, Sivas University of Science and Technology

Department of Electrical and Electronics Engineering Department/Research, Turkey

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Published

2023-07-20

How to Cite

AKKAYA, S. (2023). Empirical Investigations: Power Quality Disturbance Classification. International Conference on Applied Engineering and Natural Sciences, 1(1), 320–324. https://doi.org/10.59287/icaens.1014