Probabilistic Modeling of Single High‐Power Loads

Ribeiro, Paulo F.

doi:10.1002/9780470746752.ch7

Cited by 2 publications

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, since supraharmonics are detected from source as primary or secondary emissions [16], the statistical characterization may be helpful to individuate and characterize these two hidden regimes. The statistical characterization of supraharmonics is handy in any of these frameworks, but it is still unexplored (it is worth noting that the statistical characterization of the low-frequency harmonics has been extensively treated instead [17][18][19]).…”

Section: Introductionmentioning

confidence: 99%

Statistical Characterization of Supraharmonics in Low-Voltage Distribution Networks

Falco

Varilone²

2021

Applied Sciences

View full text Add to dashboard Cite

Modern power systems are subject to waveform distortions that include spectral components (supraharmonics) in the range of 2–150 kHz. Due to the lack of regulation in this range and since supraharmonics may follow time-varying patterns, the operators can take advantage of the statistical characterization of supraharmonics, e.g., for determining convenient power quality limits or to analyze the residual capacity of networks toward further installations of power electronic converters. This paper studies the statistical characterization of supraharmonics in low-voltage distribution networks, considering both the overall supraharmonic distortion (through the characterization of the total supraharmonic distortion index) and individual supraharmonic components. Several probability distributions are proposed and compared, also considering multimodal distributions that can fit more general scenarios in which the supraharmonic emissions follow regime patterns. The outcome of numerical experiments based on publicly available data collected at actual low-voltage distribution networks suggests that multimodal distributions are useful in characterizing supraharmonics in most cases, with acceptable goodness of fitting even in the presence of stair-shaped empirical distributions. This paper can serve as a starting point for the development of probabilistic power system analysis tools accounting for supraharmonic emissions and for the convergence toward standardization in the 2–150 kHz range.

show abstract

Section: Introductionmentioning

confidence: 99%