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Time-invariant and time-varying filters versus neural approach applied to DC component estimation in control algorithms of active power filters

Author

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  • Grabowski, Dariusz
  • Maciążek, Marcin
  • Pasko, Marian
  • Piwowar, Anna

Abstract

This paper presents an application of digital filters and neural networks to the extraction of a DC signal component. This problem arises, among others, in control of active power filters (APF) used for power quality improvement. Solutions to the basic problem of DC component estimation are well-known and so the difficulty of the task comes rather from the required minimization of the calculation time. It should ensure fast reaction of the control system to load changes. As a result, lower value of the current total harmonic distortion coefficient (THD) and better efficiency of the APF can be obtained.

Suggested Citation

  • Grabowski, Dariusz & Maciążek, Marcin & Pasko, Marian & Piwowar, Anna, 2018. "Time-invariant and time-varying filters versus neural approach applied to DC component estimation in control algorithms of active power filters," Applied Mathematics and Computation, Elsevier, vol. 319(C), pages 203-217.
    • Handle: RePEc:eee:apmaco:v:319:y:2018:i:c:p:203-217
    DOI: 10.1016/j.amc.2017.02.029
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    Cited by:

    1. Eslami, Ahmadreza & Negnevitsky, Michael & Franklin, Evan & Lyden, Sarah, 2022. "Review of AI applications in harmonic analysis in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).

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